GOVERNMENT OF UGANDA
HEALTH STATUS AND ASSOCIATED FACTORS
Thematic Series
Based on the National Population and Housing Census 2014
Uganda Bureau of Statistics Kampala, Uganda
November 2017
This monograph presents the health conditions of the people in Uganda, using data from the National Population and Housing Census (NPHC) 2014. It makes use of already published data and a range of special tabulations produced for this monograph. Reference to international data has been made to enable the information reflect the regional and global context. The National Population and Housing Census (NPHC) 2014 was undertaken by the Uganda Bureau of Statistics (UBOS). Additional information about the Census may be obtained from the UBOS Head Office, Statistics House. Plot 9 Colville Street, P. O. Box 7186, Kampala, Uganda; Telephone: +256-414 706000 Fax: +256-414 237553; E-mail: [email protected] ; Website: www.ubos.org
Recommended Citation
Uganda Bureau of Statistics 2017, The National Population and Housing Census 2014 – Health status and Associated factors. Thematic Report Series, Kampala, Uganda.
Health Status and Associated Factors i
TABLE OF CONTENT TABLE OF CONTENT ...... ii LIST OF FIGURES, TABLES AND MAPS ...... v FOREWORD ...... viii PREFACE ...... x ACRONYMS ...... xi INTRODUCTION ...... 1 1.1. Background ...... 1
1.2. Presentation of results ...... 2
FERTILITY AND BIRTH CERTIFICATION ...... 4 Key Findings ...... 4
2.1. Current Fertility ...... 4
2.2. Fertility trends ...... 7
2.3. Infertility/childlessness ...... 9
2.4. Birth Certification ...... 10
MARRIAGE AND CHILD BEARING ...... 13 Key Findings ...... 13
3.1. Child Marriage ...... 13
3.2. High Risk Births ...... 15
3.3. Adolescent Motherhood ...... 16
3.4. Availability of Youth Friendly Services ...... 17
ENVIRONMENTAL HOUSEHOLD HEALTH ...... 19 Key Findings ...... 19
4.1. Condition of Buildings ...... 19
4.1.1. Overcrowding ...... 20
4.1.2. Temporary and permanent dwelling units ...... 21
4.2. Source of Water for Drinking ...... 23
4.2.1. Main drinking water source ...... 23
4.2.2. Distance to Main Source of Water for Drinking ...... 27
4.3. Sanitation Facilities...... 28
4.3.1. Toilet facilities ...... 28
Health Status and Associated Factors ii
4.3.2. Bathroom facilities ...... 31
4.3.3. Solid waste disposal ...... 34
4.4. Cooking Arrangements ...... 35
4.4.1. Fuel used for cooking ...... 35
4.4.2. Type of kitchen ...... 36
4.5. Food Consumption ...... 38
4.5.1. Meals taken by a household in a day ...... 38
4.5.2. Sugar Intake ...... 40
4.5.3. Salt Intake ...... 41
4.6. Child warmth ...... 43
4.7. Use of shoes ...... 44
4.8. Mosquito nets ...... 45
4.9. Social problems affecting communities ...... 47
4.10. Distance to health facilities ...... 48
POPULATION HEALTH STATUS AND OUTCOMES ...... 50 Key Findings ...... 50
5.1. Trend/Evolution of life expectancy at birth between 1969 and 2014 ...... 50
5.2. The mortality pattern in Uganda...... 53
5.2.1. Mortality by Specific Age Groups ...... 54
5.2.2. Childhood mortality ...... 55
5.2.3. Adult Mortality ...... 59
5.2.4. Older Persons Mortality ...... 61
5.2.5. Pregnancy-Related Deaths ...... Error! Bookmark not defined.
5.3. Causes of death ...... 64
POLICY FRAMEWORK, CONCLUSIONS AND POLICY IMPLICATIONS ...... 68 6.1. Policy frameworks ...... 68
6.2. Conclusion ...... 68
6.3. Policy Implications ...... 69
References ...... 71
Health Status and Associated Factors iii
Glossary of terms and definitions ...... 73 APPENDICES...... i List of Contributors to this thematic report ...... xl The Household Questionnaire and Codelist for the National Population and Housing Census 2014 42
Health Status and Associated Factors iv
LIST OF FIGURES, TABLES AND MAPS Figures Figure 2.1: Fertility by background characteristics ...... 6 Figure 2.2: Total Fertility Rates, 1969-2014 ...... 8 Figure 2.3: Age Specific Fertility Rates (ASFRs), 2002 – 2014 ...... 9 Figure 2.4: Trends in Childlessness among women 45-49 years old ...... 9 Figure 2.5: Percentage Distribution of Childlessness by region ...... 10
Figure 3.1: Percentage distribution of children aged 10-17 years who are currently married ...... 14 Figure 3.2: Percentage distribution of LC Is with Youth Centre and Community Centre by region ...... 18
Figure 4.1: Distribution of Households that are overcrowded by residence ...... 21 Figure 4.2: Percent distribution of Households by Main Source of Drinking Water and Place of Residence ...... 24 Figure 4.3: Percent Distribution of Households using improved Toilet Facilities and place of residence30 Figure 4.4: Percentage distribution of Households with shared Toilet Facility by Selected Characteristics ...... 31 Figure 4.5: Percent Distribution of types of kitchen used by households ...... 37 Figure 4.6: Percent Distribution of households that use firewood by type of kitchen ...... 38 Figure 4.7: Percentage distribution of households by average number of meals taken per day ...... 39 Figure 4.8: Percentage of households with all members consuming sugar at least once a day ...... 41 Figure 4.9: Percentage of households with salt available ...... 42 Figure 4.10: Percentage of households with every Child having a separate blanket ...... 43 Figure 4.11: Percentage of households with every member having at least one pair of shoes ...... 45 Figure 4.12: Distribution of Households by Ownership of Mosquito Nets and source of nets by Residence and Sub-Region ...... 46 Figure 4.13: Percent Distribution of LCIs by health related social problems affecting residents ...... 48
Figure 5.1: Life Expectancy at Birth by Census Year 1969- 2014 ...... 51 Figure 5.2: Life Expectancy as of Census 2014 ...... 51 Figure 5.3: Probability of dying by Age group and Sex ...... 54 Figure 5.4: Census 2014 questions ...... 55 Figure 5.5: The set of questions asked and from which adult and pregnancy related death are computed ...... 59 Figure 5.6: Life expectancy at age 60 (e60) by sex ...... 62 Figure 5.7: Proportion of adult female deaths due to maternal causes ...... 64 Figure 5.8: Distribution of reported causes of death ...... 65 Figure 5.9: Distribution of reported cause of death as disease by age and sex ...... 65 Figure 5.10: Distribution of reported cause of death as accident by age and sex ...... 66 Figure 5.11: Distribution of reported cause of death as violence by age and sex ...... 67 Figure 5.12: Distribution of reported cause of death as witchcraft by age and sex ...... 67
Health Status and Associated Factors v
Tables Table 2.1: Birth Registration of children below 5 Years by Background Characteristics ...... 11
Table 3.1: proportion of women aged 15-49 years that had high risk pregnancy ...... 15
Table 4.1: Percent distribution of overcrowd households by selected Background characteristics 20 Table 4.2: Percent Distribution of Households by Selected Characteristics and Status of the Dwelling Unit ...... 22 Table 4.3: Percent distribution of Households by source of drinking water ...... 25 Table 4.4: Distribution of Households by distance to Main Source of Drinking Water by Residence and Sub-Region ...... 27 Table 4.5: Distribution of Households by type of Toilet Facility and Selected Characteristics ...... 29 Table 4.6: Percentage distribution of households by residence, region, sex, and main type of bathroom used ...... 32 Table 4.7: Distribution of households whose members use soap to bath by sex, residence, region, wealth status ...... 33 Table 4.8: Distribution of Households by Method of Solid Waste Disposal and Selected Characteristics ...... 35 Table 4.9: Distribution of Households by Main Source of Fuel for Cooking and Selected Characteristics ...... 36 Table 4.10: Distribution of Households within a 5 Kilometer distance to a health facility by Selected Characteristics ...... 49
Table 5.1: Childhood mortality 1969-2014 ...... 56 Table 5.2: Pregnancy Related Mortality ...... 63 Table 5.3: Pregnancy Related Mortality by region ...... 63
Table A.1: Total Fertility Rate and possession of a birth certificate by district and place of residence ...... i Table A.2: Adolescent fertility rate and early marriages by district ...... v Table A.3: Distribution of households by Overcrowding Status and selected Background characteristics ...... ix Table A.4: Source of Drinking water by District ...... xii Table A.5: Distribution of Households by Distance to drinking Water source by district ...... xvi Table A.6: Type of Kitchen at Household ...... xx Table A.7: Distribution of households by number of Meals taken in a day ...... xxiv Table A.8: Consumption of Sugar and availability of salt in the Household ...... xxviii Table A.9: Distribution of households by type of bathroom and use of soap for bathing ...... xxxii Table A.10: Infant Mortality, Under Five Mortality and Life Expectancy at Birth by District ...... xxxvi
Health Status and Associated Factors vi
Maps Map 2.1: Total Fertility Rate by District ...... 7 Map 2.2: Percent distribution of children under age 5 who possess a birth certificate ...... 12
Map 3.1: Percent distribution of Adolescent Motherhood age 12 to 19 years ...... 17
Map 4.1: Distribution of Temporary Dwelling Units by District ...... 23 Map 4.2: Distribution of number of Households using Improved Drinking Water Sources ...... 26 Map 4.3: Percent distribution of households within less than 1 km to a water source...... 28 Map 4.4: Percent distribution of households whose members consume one meal a day ...... 40 Map 4.5: Percent distribution of households with every Child having a separate blanket...... 44 Map 4.6: Percent distribution of households that own a mosquito net ...... 47
Map 5.1: Female Life Expectancy at Birth as of Census 2014 ...... 52 Map 5.2: Male Life Expectancy at Birth as of Census 2014 ...... 53 Map 5.3: Under five Mortality by district ...... 57 Map 5.4: Infant Mortality by district ...... 58 Map 5.5: Male Adult Mortality by district ...... 60 Map 5.6: Female Adult Mortality by district ...... 61
Health Status and Associated Factors vii
FOREWORD
The utility of statistics for policy formulation, decision-making, monitoring and evaluation of socio-economic development programmes and projects has long been recognised in Uganda. There is also increase in the demand for statistics in the country, including indicators to inform progress in National and International agenda like the National Development Plan II (NDP II), Agenda 2063 among others. To respond to this demand, the Bureau has over the years developed systems to facilitate the production of statistics through the conduct of censuses, surveys and compilation of data from administrative sources. As the coordinator of the National Statistics System, the Bureau has also together with its stakeholders in the National Statistical System (NSS) developed a National Standard Indicators (NSI) Framework that contain a list of indicators that will be closely produced over time.
The 2014 Population and Housing Census was the fifth census to be undertaken in Uganda since independence in 1962. The broad objective of the 2014 National Population and Housing Census (NPHC) was to ensure the availability of demographic, housing and socio-economic bench-mark data at the national and sub-national levels for planning. Beyond providing benchmark data for planning, detailed analysis of the census will enhance understanding of the effectiveness of the various interventions initiated by Government and its partners in improving the lives of Ugandans.
To facilitate analysis in the report the districts have been grouped into 15 sub-regions with similar characteristics. The sub-regions are Kampala, Central1, Central2, Bukedi, Busoga, Elgon, Teso, Karamoja, West Nile, Lango, Acholi, Ankole, Kigezi, Bunyoro and Toro. An attempt has also been made to present the patterns of the findings by background characteristics including by rural/urban residence, the 15 sub-regions, sex, and wealth status among others. When presenting the household characteristics, the differentials were presented by selected socio-economic characteristics and the sex of the head. In showing the spatial patterns and differentials, information is presented by the Uganda’s 122 Districts as at 1st July 2017.
Comparison with the results from the earlier censuses, some trend analysis has been undertaken in the report contrasting the 2014 Census indicators with those released under previous censuses. However, with the ever changing rate of the administrative set up of the country, it was not possible to make this comparison below District level. In order to support the planning process, the results from the Census 2014 are being released in phases as and when they become available. The Provisional Results Report was released in November, 2014 followed by the Final Results Report which was released in March 2016. The Sub- County Reports were released in June 2016 and the Area Specific Profile Series in July 2017. These reports collectively provided information on the characteristics of the population and households at National and sub-county levels.
Health Status and Associated Factors viii
In addition to this report, the sister Thematic Reports and the other reports mentioned above that have already been published, the Bureau will be producing the following:
(i) The Census Administrative Report (ii) Census Atlas (iii) Post Enumeration Survey Report
UBOS wishes to express its gratitude to all stakeholders and Development Partners (UK AID, UNFPA, UNICEF).
The value of statistics is appreciated on its use, the Bureau, therefore appeals to all stakeholders to use the information contained in this and other census reports to inform policy and decision making so as to benefit the whole public.
Together We Count
Ben Paul Mungyereza
EXECUTIVE DIRECTOR
Health Status and Associated Factors ix
PREFACE For Uganda, bottlenecks to achieving effective coverage of high impact maternal and new-born interventions at scale have been identified in the Reproductive, Maternal, Newborn, Child and Adolescent Health (RMNCAH) Investment Case and the Health Sector Development Plan. These include leadership, human resources, service delivery, information systems, supply chain systems and economic prosperity. This thematic report by the Uganda Bureau of Statistics, providing an in-depth analysis of the health status in Uganda is timely. Complemented by other thematic monographs on Education and Population Dynamics, it explains the social determinants of health and the quality life based on the 2014 Census report. The Monograph provides an in-depth analysis of fertility, child marriage, pregnancy risks and the different aspects of social and environmental determinants of health that highly impact on health and survival of women, children and adolescents. Over the years, there has been a progressive improvement in most of the health indicators in Uganda, though with glaring regional variations. Urgent efforts are therefore needed to tackle first the immediate causes of death and morbidity for the majority of women, newborns, adolescents and youth, while putting in longer-term efforts to strengthen the health system and working on the social determinants of health that majorly lie outside the health sector. The data highlighted in this analysis is important for policy makers, planners and service providers to plan, monitor and evaluate health programmes on a regular basis, and guide on coming up with strategies and areas of investment for short, medium and long term so as to improve quality health care systems at all levels. This should translate into the attainment of health sector goals at local, national and global goals. There is need to prioritize interventions with emphasis on efficiency and effectiveness of the health system in partnership with Development Partners, the Civil Society Organizations, the Private Sector, Community and other relevant stakeholders in quest to achieve the sustainable development goals. UNFPA appreciates the Uganda Bureau of Statistics for coordinating and providing technical support to the development of the health monographs.
Alain SIBENALER Representative United Nations Population Fund (UNFPA) Uganda
Health Status and Associated Factors x
ACRONYMS ACEB Average Number of Children Ever Born AIDs Acquired Immune Deficiency Syndrome ASFR Age Specific Fertility Rate CBR Crude Birth Rate GFR Gross Fertility Rate HDI Human Development Index HIV Human Immunodeficiency Virus HSDP Health Sector Development Plan IMR Infant Mortality Rate KM Kilometre LC 1 Local Council 1 LLIN Long Lasting Insecticide Treatment Nets MDAs Ministries, Departments and Agencies MMR Maternal Mortality Rate NDP II National Development Plan NHP National Health Plan NIRA National Identification and Registration Authority NPHC National Population and Housing Census PWDs Persons With Disabilities RMNCH Reproductive, Maternal, Neonatal and Child healthcare SRH Sexual Reproductive Health SDGs Sustainable Development Goals SIPs Sector Investment Plans TFR Total Fertility Rate UBOS Uganda Bureau of Statistics UDHS Uganda Demographic and Health Survey UHC Universal Health Coverage UN United Nations UNHS Uganda National Household Survey
Health Status and Associated Factors xi
KEY CENSUS INDICATORS FOR UGANDA, 2014 Population Size
Total population in 2014 was 34.6 million and projected at 37.7 million in mid-2017 The females constituted 51% of the Population Population density was 173 persons per square kilometer Population Composition
Children below 18 years constituted 55% of the population Youths (persons 18 – 30 Years) constituted 23% of the population The Age Dependency Ratio was 103% Population Change
Total Fertility Rate (TFR) was 5.8 children per woman Infant Mortality Rate (IMR) was 50 infant deaths per 1,000 live births Maternal Mortality Rate (MMR) was 380 death per 100,000 live births The average annual population growth rate was 3.0%
Population Characteristics
The Literacy Rate was 72.2% (of the population aged 10 years and above) 8% of the Children were orphaned 12.5% of the Primary School Age Children (6 - 12 years) were not attending school 12.5% of persons had at least one form of disability. Household Characteristics
Nearly one-quarter (25%) of the households were living in urban areas The mean household size was 4.7 persons 72% of the households had access to an Improved Water Source 8% of the households had no access to a toilet facility 21.1% of the households had access to electricity 94% of the households used firewood or charcoal for cooking 69% of the households depend on Subsistence Farming as their main source of livelihood. 32% of the households owned a bicycle
Agricultural Characteristics
80% of the households were involved in Agriculture
Health Status and Associated Factors xii
CHAPTER INTRODUCTION ONE:
1.1. Background
Health is an integral constituent of human capital and the entire development process of any country. It is crucial in boosting economic growth, per capita income and overall development through enhancement of labour productivity. Uganda’s Second National Development Plan (NDP II) that covers 2015/16–2019/20 recognises health as a key human capital development dimension and a priority development area essential for attaining a middle income status by 2020 and the long term vision of a modern and prosperous country by 2040. The current Health Sector Development Plan (HSDP) covers 2015/16 – 2019/20 and provides the strategic focus and direction for the development of the health sector in the medium term. It is through the HSDP that the health component of the NDP II, and the National Health Policy (NHP) are designed to be operationalised. The current national aspiration of Universal Health Coverage as stipulated in the HSDP is meant to contribute to a healthy and productive population and it is aligned to the global health agenda enshrined in the Sustainable Development Goals (SDGs). This monograph analyses and discusses information on potential health risks and health status in Uganda as reported in the 2014 National Population and Housing Census (NPHC). The information provides insights that are important for healthcare planning and service delivery. It also captures indicators that are pertinent for assessing progress in the health sector. For example it captures core health outcome metrics such as life expectancy, infant and child mortality, and maternal mortality. The monograph analyses critical health risk factors due to prevailing socio-economic and environmental conditions that potentially predispose sections of Ugandan households to different health hazards. These conditions have direct policy relevance within the local context of the HSDP and NDP II as well as within the monitoring of progress in the implementation of the Sustainable Development Goals (SDG). For example, the conditions have policy relevance to water, sanitation and hygiene, housing conditions and over-crowding, use of clean fuels and technology, solid waste disposal, and food availability in households. The rest of the monograph is organized as follows. Chapter two discusses the health implications of fertility and birth registration. Chapter three presents marriage, pregnancy, high risk births, and their health implications. Chapter four discusses social and environmental household and community health. Chapter five presents health outcomes focusing on mortality and cause of death. Chapter six presents policy frameworks for the health sector, conclusion and policy implications.
Introduction 1
1.2. Presentation of results The results have been presented as numbers and proportions. Most of the findings have been disaggregated by sex, place of residence, district and 15 sub-regions. The district groupings have been grouped into sub-regions as follows;
• Central 1: Butambala, Gomba, Mpigi, Bukomansimbi, Kalangala, Kalungu, Lwengo, Lyantonde, Masaka, Rakai, Sembabule, Wakiso, Kyotera • Central 2: Buikwe, Buvuma, Kayunga, Kiboga, Kyankwanzi, Luwero, Mityana, Mubende, Mukono, Nakaseke, Nakasongola • Kampala: Kampala • Busoga: Bugiri, Namutumba, Buyende, Iganga, Jinja, Kaliro, Kamuli, Luuka, Mayuge, Namayingo • Bukedi: Budaka, Butaleja, Kibuku, Pallisa, Tororo, Busia, Butebo • Elgon: Bulambuli, Kapchorwa, Kween, Bududa, Manafwa, Mbale, Sironko, Bukwo, Namisindwa • Teso: Amuria, Bukedea, Katakwi, Kumi, Ngora, Soroti, Kaberamaido, Serere • Karamoja: Abim, Amudat, Kaabong, Kotido, Moroto, Nakapiripirit, Napak • Lango: Alebtong, Amolatar, Dokolo, Lira, Otuke, Apac, Kole, Oyam • Acholi: Agago, Amuru, Gulu, Lamwo, Pader, Kitgum, Nwoya, Omoro • West Nile: Adjumani, Arua, Koboko, Maracha, Moyo, Nebbi, Yumbe, Zombo, Pakwach • Bunyoro: Buliisa, Hoima, Kibaale, Kiryandongo, Masindi, Kagadi, Kakumiro • Toro: Bundibugyo, Kabarole, Kasese, Ntoroko, Kyenjojo, Kamwenge, Kyegegwa, Bunyangabu • Kigezi: Kabale, Kisoro, Kanungu, Rukungiri, Rubanda, Rukiga • Ankole: Buhweju, Bushenyi, Ibanda, Isingiro, Kiruhura, Mbarara, Mitooma, Ntungamo, Rubirizi, Sheema
Introduction 2
MAP OF UGANDA SHOWING 15 SUB REGIONS
Introduction 3
CHAPTER FERTILITY AND BIRTH CERTIFICATION TWO:
Key Findings • The current total fertility rate in Uganda is 5.8 children per woman: 4.1 children in urban areas and 6.5 children in rural areas.
• Fertility peaks in the age group 20-24 years and gradually declines among women in their thirties through forties. • Fifteen (15%) of the adolescents (aged 12-19 years) have ever given birth.
• Childlessness has decreased from 6.6 percent to 4.0 percent in the last 23 years. • Slightly over one in every three children below 5 years of age possesses a birth certificate indicating a very low level of birth registration in the country.
2.1. Current Fertility This chapter discusses current, cumulative, and past fertility in terms of trends, levels and patterns observed in the 2014 Census as well as in other past censuses and Demographic and Health Surveys. Information on fertility levels, patterns and trends experienced by a country is important for socio-economic planning, monitoring and evaluating programmes. To formulate or evaluate policies concerning population growth, information is needed not only on the number of births, but also on trends of birth rates and other measures of fertility over time and, equally importantly, on the age structural distribution and changes over time, of the population. Total Fertility Rate (TFR) is cited as a key performance indicator in the Health Sector Development plani (HSDP) 2015/16 -2019/20 for measuring the impact on health (particularly reproductive and maternal health) in order to contribute to the production of a healthy human capital for wealth creation through provision of equitable, safe and sustainable health services. In general, fertility is a crucial indicator for understanding population change and how it relates to health and overall development. In this report, the current fertility is demonstrated using two measures i.e: the Age-Specific Fertility Rate (ASFR) and the Total Fertility Rate (TFR). The ASFR provides the age pattern of fertility and TFR is the number of live births (children) a woman will have borne at the end of her reproductive life if she experiences the current age pattern of child bearing. Fertility as a health issue High fertility has a negative effect on maternal and neonatal health care and adverse consequences on neonatal survivalii. While high fertility may affect the quality of an individual's life socially and psychologically, it should be recognized that having many children born exposes women to higher risk of diseases thus affecting maternal morbidityiii. Research has shown associations between high
Fertility and Birth Registration 4
parity and several diseases. Examples include cardiovascular diseaseiv v, urinary incontinencevi and obesityvii. The United Nations Department for Economic and Social Affair (UNDESA) categorizes a country as having high fertility if its TFR is above 5 children per woman. Figure 2.1 shows Uganda’s Total Fertility Rate is high, standing at 5.8, which is higher than the Sub-Saharan African average of about 4.981, and doubles the standard the replacement2 fertility level. This implies that a Ugandan woman who is at the beginning of her childbearing years would give birth to an average of six children by the end of her reproductive period if fertility levels remained the same as those observed in the 2014 Census. High fertility levels create a large and unsustainable population, and also exerts enormous pressure on healthcare service delivery, thus threatening efforts and progress towards the national health goal of Universal Health Coverage. The problem of high fertility is striking among the uneducated women and those in rural areas, indicating a close relationship between fertility level and the socio-economic status of women. For instance, a TFR of 6.5 for women in rural areas which is more than two births higher than the rate of 4.1 for women in urban areas. Pertaining to education, women with no formal education give birth to an average of 7.0 children in their reproductive lifetime, compared with 4.1 children per woman for those who attended secondary school or higher.
1 2014 World Bank estimate of TFR for Sub-Saharan African countries 2 According to WHO standards, the fertility replacement level is about 2-3 children per woman.
Fertility and Birth Registration 5
Figure 2.1: Fertility by background characteristics
Total 5.8
Secondary+ 4.1 Primary 6.6 No Education 7
Kigezi 4.8 Bunyoro 7.5 Ankole 5.1 Tooro 6.1 Karamoja 7.5 Lango 4.4 Acholi 7 West nile 6.2 Teso 7.3 Elgon(Bugisu) 6.1 Bukedi 7 Busoga 6.9 Central 5.2 Kampala 3.3
Rural 6.5 Urban 4.1 0 1 2 3 4 5 6 7 8
Map 1 and appendix table A1 shows that fertility is highest (above 8 children per woman) in Amudat. Kaabong, Koitdo, Agago, Lamwo, Amuru and Nwoya district. It is lowest (below 4.6 children per woman) in Kampala, Wakiso, Mbarara, Bushenyi, Ntungamo, Rukiga and Kabale districts.
Fertility and Birth Registration 6
Map 2.1: Total Fertility Rate by District
2.2. Fertility trends The Health Sector Development plan (HSDP) 2015/16 -2019/20 aims to reduce the TFR to 5.1 children per woman by the year 2020. Figure 2.2 shows trends in Total Fertility Rate in Uganda by comparing the results over the Census years. The Total Fertility Rate has dropped from 7.1 births per woman in 1991 to 5.8 births in 2014, after stagnating at the former level from 1969 to early 1990s. This demonstrates fertility reduction over the period, signaling the possibility of achieving the HSDP target by 2020. However, efforts towards stimulating an accelerated decline are essential given the observed gradual pattern of fertility reduction. Rapid fertility decline is a requisite for achievement of the target set in the HSDP, and for triggering demographic dividend for the country.
Fertility and Birth Registration 7
Figure 2.2: Total Fertility Rates, 1969-2014
8 7.1 7.1 7.1 6.9 6.9 7.0 7 6.7 6.2 5.8 6
5
4
3 Total Fertility Rate TotalFertility 2
1
0 1969* 1988 1991* 1995 2000 2002* 2006 2011 2014* Year
Note: * is a population census year and the rest are Demographic and health Survey
Figure 2.3 shows that in Uganda, childbearing starts early with women aged 15-19 years old, and it peaks in the 20-24 years age group. Fertility then decelerates with age in the late thirties and forties. This implies that younger women are giving more births compared to their older counterparts. The same trend is observed in both 2002 and 2014 Census. The observed ASFR pattern is fairly consistent with standard pattern in most developing countries including those within the region such as Tanzania. What is of policy concern is childbearing peaking at an early age (i.e. 15 to 24 years). Although Figure 2.3 shows a higher decline in ASFRs in the younger age groups (15-19, 20-24 and 25-29) compared to older age groups, the ASFRs for the younger age groups are still high, and this calls for intensifying efforts aimed at accelerated reduction in early marriages and more especially early childbearing, given the associated healthcare risks.
Fertility and Birth Registration 8
Figure 2.3: Age Specific Fertility Rates (ASFRs), 2002 – 2014
0.004 0.004 0.003 0.003
0.002 ASFRs 0.002 0.001 0.001 0.000 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49
2002 2014
2.3. Infertility/childlessness Infertility is a medical condition whose causes cannot be easily established using census data. However, the Ugandan society is characterized by early and almost universal marriage as well as high fertility. Therefore, having had no children at the end of one’s reproductive life (age 45-49 years of age) is unlikely to be voluntary and is taken as a proxy for infertility. Research has shown that childless women experience poorer physical, mental health and well-being during the peak reproductive yearsviii
Figure 2.4: Trends in Childlessness among women 45-49 years old
6.6 Figure 2.4 also shows that 6.2 childlessness has generally reduced overtime from 6.6 4.6 percent in 1991 to four (4) 4.1 4.0 percent in 2014 among all women aged 45 – 49 years. 3.1 It is slightly among the ever married women.
Census 1991 Census 2002 Census 2014 All women Ever married
Fertility and Birth Registration 9
Figure 2.5 shows that childlessness is highest in kampala at about 7 percent. This information is useful to avoid involuntary childlessness using targeted medical interventions and other forms of assisted reproductive technology.
Figure 2.5: Percentage Distribution of Childlessness by region
Kigezi 4.2
Bunyoro 3.0
Ankole 2.7
Toro 2.5
Karamoja 3.3
Lango 3.7
Acholi 3.2
West Nile 3.5 Region Teso 4.2
Elgon 4.5
Bukedi 4.2
Busoga 3.4
Central2 3.6
Central1 3.9
Kampala 6.9
2.4. Birth Certification Birth registration provides useful information for public health planning and programming. The birth registration information is crucial for planning and evaluating public health programmes. For example, given the wealth of health or medical information captured in the birth registration certificate, it provides insights that are relevant for establishing interventions capable of addressing conditions associated with child or infant mortality. One of the key interventions for building a harmonized and coordinated health information system in the HSDP is improvement of the operational capacity for birth and death registration in collaboration with the National Identification and Registration Authority (NIRA). The key measurement indicator for this intervention is the birth registration rate, with a target of 50 percent set to be achieved by 2019/20. The 2014 census results reveal that about one third of all persons (28 percent) possess a birth certificate. In terms of child registration, 30 percent of children below the age of 5 years possess a birth certificate, an improvement from the 17 percent observed in the 2011 UDHS. Despite the improvement, overall, the current level of birth registration of children (30%) is low, and this hampers effective planning at different levels especially in regard to public health programming.
Fertility and Birth Registration 10
Table 1.1 shows that Kampala (47%) and Acholi region (44%) had the highest percentage of children with certificates but in terms of numbers Central 1 had the highest number of children who are registered (108,386 children). On the other hand, Bunyoro region had the lowest percentage of children with certificates (17%) but in terms of numbers, the smallest number of children with certificates is in Kigezi and Karamoja region (slightly over 27,000). Table 2.1 also shows that there seems to be no discrimination by disability status in terms of birth certification as seen from the almost the same proportion of registered children.
Table 2.1: Birth Registration of children below 5 Years by Background Characteristics
Number of children with a Percent of under 5 who have a Total Number of children below 5 birth certificate birth certificate years
Place of residence
Urban 248,513 39.0 637,440
Rural 634,364 27.5 2,309,153
Sub Region
Kampala 47,533 46.8 101,553
Central 1 108,386 30.6 353,880
Central 2 87,799 28.6 306,575
Busoga 98,350 30.0 327,775
Bukedi 47,179 27.3 173,087
Elgon 32,070 22.1 144,992
Teso 59,442 37.1 160,041
West Nile 80,261 35.3 227,242
Acholi 56,272 43.8 128,516
Lango 64,479 37.8 170,522
Karamoja 27,551 32.2 85,637
Toro 65,691 28.0 234,796
Ankole 49,007 21.1 231,742
Bunyoro 31,818 16.7 190,205
Kigezi 27,039 24.6 110,030
Disability Status of child
With No Disability 537,376 30.9 1,740,073
With Disability 21,931 31.5 69,682
Map 2 and appendix table A 1 shows that the following districts have more than half of the children under age 5 who have birth certificates: Yumbe (58%), Katakwi (55%), Moyo (52%), Agago (51%), Lamwo (51%), Otuke (51%) and Kitgum (50%). While Bullisa district had the lowest percentage of only 7 percent that reported that they had a birth certificate.
Fertility and Birth Registration 11
Map 2.2: Percent distribution of children under age 5 who possess a birth certificate
.
Fertility and Birth Registration 12
CHAPTER MARRIAGE AND CHILD BEARING
THREE:
Key Findings • In Uganda about one in every ten fifteen- year-olds are in a marriage and rural women are more likely to engage in early marriage than the urban women. • Women in the rural areas are twice as likely to produce too many children compared to the urban women. • Women who have never been to school are likely to start child bearing very early (11%) and half of them have too many children (four or more births). • Bunyoro (19%) and Toro (18%) region had the highest percentage of adolescents (age 12-19 years) that have ever given birth.
3.1. Child Marriage The NDP II recognizes early onset of marriage and childbearing as one of the reasons for high fertility in Uganda. Dire consequences of early childbearing are felt by society as well as the families directly affectedix. Studies suggest that early parenthood is detrimental to physical health in later life especially in physiological terms. Early childbearing is thus associated with poor maternal and child health outcomes such as preterm birth and low birth weight, which in turn can aggravate other outcomes like infant, child and maternal mortality. Figure 3.1 shows that in Uganda about one in every ten 10-17 year olds were in a marriage (7%). Figure 3.1 also shows that lack of education is also seen to have some influence on early marriage for example, the proportion who are married reduces from 8 percent among girls as the level of education increases to 6 percent. However, when they get to secondary, some drop out of school and get married hence the increase to 10 percent of those who are married and have secondary education. This suggests that keeping teenagers in school can substantially contribute to fertility control in the country.
Marriage and Child Bearing 13
Figure 3.1: Percentage distribution of children aged 10-17 years who are currently married
9.7
7.8
6.8 6.5 5.5 5.8
3.7
2.2 1.7 1.4 1.3 1.6
Urban Rural Never Primary Secondary Uganda attended
Male Female
Appendix table A2 shows that there are 292,129 (24%) children age 10-17 years who have been sexually exposed in a marriage and are at risk of contracting sexually transmitted diseases. Worst are 30,266 children in Uganda who are either widowed or separated, reasons to this may need further investigation to inform Sexual and Reproductive health interventions. The districts of Wakiso (1,336), Arua (1,041), and Kasese (1,026) had really high numbers of children age 10 to 17 years who were either widowed, divorced or separated. Wakiso district had the highest number of early marriage exposure in Uganda of 11,865 children age 10 to 17 years. This is closely followed by the following districts that have over 6,000 children age 10 to 17 years who had been in a marriage: Arua, Mukono, Hoima, Mayuge, Kasese, Oyam, Mubende districts.
Marriage and Child Bearing 14
3.2. High Risk Births High risk births are those that are associated with the four “Too’s” namely “Too Early”, “Too Close”, “Too Many” and “Too Late”. The births that are considered Too Early are those born to women below the age of 20, “Too Close” are the births that are less than two years from the previous birth, “Too Many” are births born to women with four or more births, while the “Too Late” are births born to women aged 35 years or more. These high-risk births are highly correlated with Table 3.1: Proportion of women aged 15-49 high fertility populations and also greatly affect years that had high risk pregnancy the health of women increases exposure to the High Risk Births hazard of infant and maternal mortality. Previous Too Too Too studies have shown that High risk births have a early late many high probability of dying. They are a point of Residence concern because they play a big role as causes Urban 7.5 6.0 16.7 of both infant as well as maternal morbidity and Rural 9.1 8.3 31.7 mortality. The census did not ask for women’s Education birth histories, therefore the dimension of ‘too Never attended 11.4 7.4 53.2 close’ cannot be investigated. Primary 8.6 8.3 31.3 Results in Table 3.1 show that women in the Secondary or more 8.5 6.7 10.2 rural areas are twice as likely to produce too Region many children compared to the urban women. Kampala 6.8 5.2 6.7
This may be linked to the low uptake of Central1 8.1 6.7 14.2 contraceptives in the rural areas compared to Central2 9.3 7.3 18.2 the urban areasx. Generally, this suggests that Busoga 10.2 8.2 21.7 access to reproductive health services may be Bukedi 9.4 8.1 21.4 poor in rural areas. Table 3.2 also shows that Elgon 8.5 7.8 17.3 women who have never been to school are likely Teso 8.2 9.1 21.5 to start child bearing very early (11%) and half of them have too many children. West Nile 8.4 8.6 18.4 Acholi 9.9 9.6 20.0 Busoga, Teso and Bukedi have the highest Lango 8.7 7.7 19.7 percentage of women having too many children. Karamoja 6.4 9.8 18.5 This may be attributed to social cultural issues, Toro 9.7 8.6 19.7 and Busoga and Teso situation may also be aggravated by the highest unmet need for family Ankole 7.7 6.6 17.7 planning of 36.5% and 36.3% respectively as Bunyoro 10.6 9.3 20.2 revealed by the 2016 Uganda Demographic and Kigezi 6.4 6.4 16.0 Health Survey results. Marital status Never married 4.6 3.8 1.6 Currently married 28.8 9.4 37.0
Ever married 31.6 3.5 39.9
Total 8.7 7.8 27.4
Marriage and Child Bearing 15
3.3. Adolescent Motherhood Adolescence is the period of life during which young boys and girls progress to adulthood. All persons aged 12 to 19 years at the time of the census were considered to be adolescents. Adolescents is one the age cohorts that the HSDP has put strategic interventions in order to promote a healthy population and human capital by promoting good nutrition, sexual and reproductive health education in schools and communities. The strategies include the adolescent health strategy-2012, the Reproductive Maternal, Newborn and Child Health Sharpened Plan for Uganda (RMNCAH) - 2013 among others. Adolescent fertility is thus an issue of policy concern in Uganda. Map 3 and Appendix Table A 2 shows that the following districts have high numbers (over 10,000) of adolescents that have ever given birth; Mayuge, Mukono, Mubende, Hoima, Kasese, Arua, Kampala and Wakiso. On the other hand, where the numbers of adolescents that had ever given birth are lower, the proportion of these adolescents within the district need attention, the districts of Kalangala, Bundibugyo and Buvuma have the highest percentages (one in every four) of adolescents that have ever given birth. Adolescent health initiatives are therefore paramount in these sub-regions or areas, in order to ensure better maternal and child health outcomes. This is because babies born to adolescent mothers encounter higher risks of dying than those born to mothers in the age cohort of 20-24; and teenage mothers are prone to more health risks.
Marriage and Child Bearing 16
Map 3.1: Percent distribution of Adolescent Motherhood age 12 to 19 years
3.4. Availability of Youth Friendly Services In Uganda, 24 percent of young people (age 10-17 years) are exposed to sexual activity. Many adolescents make the transition to adulthood in good health while others do not and may face some health problems either during adolescence or later in life. Adolescents also face barriers in accessing Sexual and Reproductive Health (SRH) services. xi . Because of this, WHO has encouraged that each country, state and locality has a policy and support to encourage provision of innovative and well-assessed youth-friendly health servicesxii. This therefore creates a need to increase the number of health centres with special opening hours and a separate space for service provision for the youth.
Marriage and Child Bearing 17
Focus Group Discussion were held with the Local Council officers, and Opinion leaders at the village level to discuss topical issues that happen and affect the community. Among these was availability of youth friendly services within the LC I.
Figure 3.2 shows that 56 percent of the Local Councils (LC I) in Uganda do not have any youth friendly services. On the overall very communities reported to be having any of the components of youth friendly services. This reveals the fact that a lot needs to be done to increase on availability of youth friendly services in all communities.
Figure 3.2: Percentage distribution of LC Is with Youth Centre and Community Centre by region
Counselling Services 16
Peer Education 12
Std/Hiv/Sex Education 15
Adolescent/Youth Pregnancy Checkups 6
Post Abortion Treatment 2
Drama 11
Indoor/Outdoor Games 21
None 56
Other services 6
Marriage and Child Bearing 18
CHAPTER ENVIRONMENTAL HOUSEHOLD FOUR: HEALTH
Key Findings • People in rural areas are four times more likely to live in temporary dwellings compared to the urban (31% verses 7%) • Only 4% of the households had piped water into the dwelling as their main source of drinking water. • About eight in ten households are within less than a half kilometer from their main source of drinking water. • Majority (87%) of households in Uganda use pit latrines and only 8% of households declared that they have no toilet facility. • Two thirds of the households in Uganda (66%) either dispose waste in the garden without burning or they burn it. • Ninety-five percent of the households in Uganda use soap for bathing • Only 3 percent of the households use clean fuels (either electricity or gas) as a main source of fuel for cooking • Half of the households in Uganda have their kitchens built outside (51%) and a quarter of them use the open space outside
This chapter presents and discusses different aspects of social and environmental determinants of health for which data was collected. These are conditions or factors that can create exposure to health risks, promote health, and protect the health of the population.
4.1. Condition of Buildings Housing can impact on health in both direct and indirect ways (Shaw 2004). Overcrowding, poor dwelling conditions and inadequate basic utilities such as facilities for bathing, sewerage systems or safe drinking water, can directly impact on both physical and mental health. Indirect effects include the area or neighbourhood in which the housing is located, proximity to services and facilities, and the broader community functioning (Shaw 2004; Bailie 2007). Household conditions have a bearing upon the maintenance of privacy and health and the development of normal family living conditions. The census collected information about housing conditions such as number of rooms used for sleeping and construction materials.
Environmental Household Health 19
4.1.1. Overcrowding Overcrowding may have both direct and indirect effects. Outbreaks of disease are more frequent and more severe when the population density is high. Overcrowding can put stress on bathroom, kitchen and laundry facilities as well as on sewerage systems such as septic tanks. It can lead to the spread of infectious diseases such as meningococcal, tuberculosis, rheumatic fever, respiratory Table 4.1: Percent diseases and skin infections (Howden-Chapman & Wilson distribution of overcrowd 2000). Children living in poor or overcrowded conditions are households by selected more likely to have respiratory problems, to be at risk of Background infections, and have mental health problems, subsequently characteristics negatively impacting on a child’s development and educational Percent attainment. For example, children’s education may be affected
crowded directly, through a lack of space for homework, as well as Sex of household head indirectly because of absenteeism at school caused by illness Male 60.7 thus affecting their performance at school. Research has also Female 40.9 revealed a link between overcrowding and stress, tension, and Region sometimes family break-up; anxiety and depression; a lack of Kampala 46.3 privacy, particularly for adolescents and disrupted sleep Central1 46.5 patterns. Central2 52.1 Chaotic sleeping arrangements are an underlying cause of Busoga 64.4 many mental health effects. Bukedi 68.9 Elgon 57.2 The National Housing policy defines overcrowding as follows: Teso 66.1 “This is the occupancy of dwelling units by more persons West Nile 68.6 than they were designed to accommodate to a degree that Acholi 64.8 endangers health, safety and welfare of the occupants. An Lango 59.7 average size habitable room (7.5 sq meters) is regarded Karamoja 81.0 (by international standards) as overcrowded if occupied Toro 51.3 by more than 2 persons.” Ankole 48.8 Table 4.1 shows that six in ten male-headed households are Bunyoro 54.9 overcrowded compared to only four in ten female-headed Kigezi 42.8 households, probably because they are financially stable and Wealth Quintile attract dependants or the men have more than one family in a Lowest 72.5 household. On the other hand, there are proportionally more Second 62.3 rural than urban households that are overcrowded, the likely Middle 54.9 reason being the dwellings are usually round huts that cannot Fourth 51.3 be split into different rooms. Because of this we can see that Highest 45.0 Karamoja region has the highest percent of overcrowded households (81%) while Kigezi has the least (43%). Uganda 55.9
Environmental Household Health 20
Figure 4.1 shows that in the last 12 years overcrowding has not changed in the urban areas but has increased in the rural areas. This finding reaffirms the observation in the NDP II that the rapid increase in urban population is not matched with adequate physical plan preparation or implementation or growth and development of housing leading to overcrowding. Therefore, more effort is needed to increase housing facilities and avert overcrowding in order to ensure healthier living conditions and ultimately contribute to better human capital. Appendix table A 3 shows that the following districts have over 80 percent of the households being over crowded: Amudat, Yumbe, Nakapiripirit, Kotido and Kaabong.
Figure 4.1: Distribution of Households that are overcrowded by residence
59 56 55 56 49 48
Urban Rural Uganda
2002 2014
4.1.2. Temporary and permanent dwelling units Permanent dwelling units are those built with construction materials (roof, wall and floor) that can maintain their stability for more than fifteen years. Permanent floor materials include concrete, cement screed, tiles, wood, while permanent roof materials include roof tiles, iron sheets, asbestos and concrete whereas permanent wall materials include concrete/stones, cement blocks and burnt/stabilized bricks. Temporary dwellings are those that are built with materials that cannot maintain their stability for more than three years. These may cause health risks especially if the person sleeps on the floor, they can be affected by cold which can lead to depression and anxiety. Table 4.2 shows that people in the rural areas are three times more likely to live in temporary households compared to the urban (31% verses 7%). On the overall, temporary housing has greatly reduced from 71 percent in 2002 to 45 percent in 2014. The following regions have the
Environmental Household Health 21
highest percentage of dwelling units that are temporary: Teso (69%), Karamoja (76%), Lango (64%), Acholi (74%), West Nile (60%) while the Elgon (75%), Toro (74%), Ankole (71%) and Kigezi (84%) regions have high percentage of semi-permanent structures. These findings call for targeted interventions to further improve people’s housing condition, especially in rural areas, as well as the most affected sub-regions.
Table 4.2: Percent Distribution of Households by Selected Characteristics and Status of the Dwelling Unit
Selected Status of Dwelling Unit Characteristics Temporary Semi-Permanent Permanent Total
Residence
Urban 24.8 6.6 68.6 100
Rural 52.4 30.5 17.2 100
Sub-Region
Central 39.4 6.3 54.3 100
Kampala 7.9 0.1 92.1 100
Central1 33.5 3.5 63.1 100
Central2 46.7 9.9 43.5 100
Busoga 51.1 17.3 31.6 100
Bukedi 46.6 31.1 22.4 100
Elgon 74.8 10.5 14.7 100
Teso 15.4 68.9 15.8 100
Karamoja 19.5 76.1 4.4 100
Lango 23.2 63.9 12.9 100
Acholi 15.6 74.1 10.3 100
West Nile 30.4 59.9 9.6 100
Bunyoro 50.4 30.4 19.2 100
Toro 73.6 10.4 16.1 100
Ankole 70.7 6.4 22.9 100
Kigezi 84.2 2.8 13.0 100
100
Census 2014 44.7 23.8 31.5 100
Census 2002 71.2 11.4 17.5 100
Map 4.1 shows the distribution of temporary dwelling units across the country. It is seen that the districts in the West Nile, Northern and Eastern part of the country have higher percentages of temporary dwellings which are associated with poor welfare status as shown by the 2016/17 UNHSxiii.
Environmental Household Health 22
Map 4.1: Distribution of Temporary Dwelling Units by District
4.2. Source of Water for Drinking This sub-section focuses on two key aspects related to availability of and access to safe and/or clean drinking water.
4.2.1. Main drinking water source Having enough water for drinking and personal hygiene is essential, but quantity by itself is not sufficient. The quality of the water is also a crucial health issue. Drinking unclean water is a health threat to both adults and children, but the threat is more substantial to children as adults have stronger immunity.
Unclean water is associated with deadly diseases for children such as diarrhea and other waterborne diseases or parasites. Consequently, one of the targets of the Sustainable
Environmental Household Health 23
Development Goals is to “achieve universal and equitable access to safe and affordable drinking water for all by 2030”, assessed in part by the proportion of the population using safely managed drinking water services. This indicator is measured by the proportion of population using an improved basic drinking water source which is located on premises and available when needed and is free of faecal (and priority chemical) contamination. The National Development Plan II has been aligned to this global agenda, thus the government of Uganda has committed itself to increase access to safe water supply both in rural and urban areas.
The most significant information from a health point of view is whether the living quarters have piped water within the premises. The census results showed that there are very few households (4%) that have piped water into the dwelling as their main source of drinking water and that three in every ten households use borehole water. Boreholes are also more popular in the rural areas (40%) compared to the urban areas (17%), a situation which may reflect the efforts made by development partners or Non-Governmental Organizations to deliver safe water in rural areas.
Figure 4.2: Percent distribution of Households by Main Source of Drinking Water and Place of Residence
16 Protected Well/Spring 17 15
34 Borehole 40 17
10 Public Taps 5 24
6 Piped Water to the Yard 1 18
4 Piped Water into Dwelling 1 11
30 Other Sources 36 17
Uganda Rural Urban
According to the metadata for SDG Indicator 6.1.1: Proportion of population using safely managed drinking water services, improved drinking water sources include the following: piped water into dwelling, yard or plot; public taps or standpipes; boreholes or tube wells; protected dug wells; protected springs and rainwater. Packaged drinking water is considered improved if households use an improved water source for other domestic purposesxiv.
Environmental Household Health 24
Table 4.3 shows that at the census time, 72 percent of the households in Uganda were using improved drinking water sources. Households in the highest wealth quintile are much more likely to have improved water sources compared to those in the lowest quintile. This implies interventions to increase access to safe water should target the poor households.
Table 4.3: Percent distribution of Households by source of drinking water
Vendor/ Improved Piped Protected Unprotected River/ Borehole Tanker Others Total Water water well/spring well/spring Stream/Lake truck source
Sex of Household head Male 19 34 17 18 8 2 3 100 71 Female 22 33 16 17 7 2 3 100 74
Wealth quintile
Lowest 2 54 11 20 12 0 1 100 67
Second 5 37 18 25 12 0 2 100 62
Middle 8 32 21 25 9 1 4 100 65
Fourth 15 36 19 19 6 1 4 100 73
Highest 56 15 13 5 1 5 4 100 88
Uganda 20 34 16 18 8 2 3 100 72
Accordingly, effective implementation of the water and sanitation component of the National Development Plan is critical for ensuring universal access to safe water supply, and in particular, more attention should be paid to the sub-regions that are most deprived in terms of improved sources of drinking water. Map 4.2 shows that the more urban areas/districts (especially those with municipalities have more trouble with access to improved drinking water sources. These include: Arua, Hoima, Kasese, Mbarara, Wakiso, Kampala, Luwero, Mukono, Buikwe, Jinja, Kamuli, Iganga, Tororo, Mbale and Lira.
Environmental Household Health 25
Map 4.2: Distribution of number of Households using Improved Drinking Water Sources
Environmental Household Health 26
4.2.2. Distance to Main Source of Water for Drinking Long distances to a source of drinking water is a potential deterrent to safe water access, and can cause a household not to have sufficient amounts of drinking water which is hazardous to their health. In this report, distance to main source of drinking water was used as a measure of access to drinking water. Table 4.4 shows that about eight in ten households are within less than a half kilometer distance to their main source of drinking water. The regions of Teso, Karamoja and Lango seem to travel longer distance to access drinking water for their households i.e. at least 30 percent of the households travel over one kilometer.
Table 4.4: Distribution of Households by distance to Main Source of Drinking Water by Residence and Sub-Region
1 Km to Less than 5 Residence/Sub-region Within less than 1 Km 5 Kms and Above Total Kms Residence
Urban 90.9 8.7 0.4 100
Rural 72.4 26.2 1.4 100
Sub-Regions
Central 83.4 15.9 0.7 100
Kampala 97.1 2.6 0.3 100
Central1 86.6 12.9 0.5 100
Central2 79.5 19.6 0.9 100
Busoga 75.5 22.7 1.8 100
Bukedi 72.1 26.4 1.5 100
Elgon 82.7 16.6 0.7 100
Teso 62.8 36.1 1.2 100
Karamoja 67.2 29.6 3.2 100
Lango 65.9 33.1 1.0 100
Acholi 82.6 16.7 0.8 100
West Nile 80.4 18.6 1.0 100
Bunyoro 77.1 22.1 0.7 100
Tooro 80.2 19.0 0.8 100
Ankole 77.9 20.6 1.5 100
Kigezi 70.4 27.4 2.2 100
Uganda 78.5 20.4 1.1 100
Map 4.3 shows that the districts with the lightest shade has majority of its households living more than a kilometer from a water source. While appendix table A5 shows that the districts of Amudat, Buyende, Isingiro and Rubanda have the least percentage of households (50% or less) that are within less than a kilometer to a source of drinking water. This means that these districts have very few sources of drinking water available in the district within the proximity of households.
Environmental Household Health 27
Map 4.3: Percent distribution of households within less than 1 km to a water source.
4.3. Sanitation Facilities Environmental health and sanitation is one of the program areas prioritized by the HSDP in order to improve the health of the population in Uganda. Sanitation is defined as the prevention of human contact with feces and the proper treatment and disposal of wastewater. Sanitation also includes promoting hygiene on a personal level through washing hands with soap. It also includes environmental aspects like solid waste management.
4.3.1. Toilet facilities A toilet may be defined as an installation for the disposal of human excreta. SDG target 6.2 aims to achieve access to adequate and equitable sanitation and hygiene for all and end open defecation, paying special attention to the needs of women and girls and those in vulnerable situations by 2030.
Environmental Household Health 28
The census 2014 collected information about the type of toilet facility that the household mainly uses. Table 4.5 shows that majority (87%) of households in Uganda use pit latrines. On the other hand, 8% declared that they have no toilet facility. Sixty-five percent use safely managed sanitation facilities i.e flush toilet, Ventilated Improved Pit latrines, Covered Pit Latrine with a Slab or Covered Pit Latrine without a Slab. The findings also show no major differentials in the type of toilet facility is used by households. Karamoja region had the least percent of safely managed sanitation facilities (19% of the households) because of the high percentage of households that have no toilet facilities (68%).
Table 4.5: Distribution of Households by type of Toilet Facility and Selected Characteristics
Covered Uncovered Covered Uncovered Selected Flush VIP Pit Latrine Pit Latrine No Toilet Pit Latrine Pit Latrine Other Total Characteristics Toilet Latrine without a without a Facility with a Slab with a Slab Slab Slab Sex of Household Head
Male Headed 2.4 9.0 20.7 33.2 6.6 18.1 1.9 8.0 100
Female Headed 3.0 10.2 21.9 30.2 6.5 16.7 2.1 9.4 100
Residence
Urban 8.6 21.8 32.4 20.5 5.3 8.1 1.0 2.4 100
Rural 0.2 4.4 16.6 37.1 7.1 21.5 2.4 10.6 100
Sub-Regions
Central 2.7 15.2 29.9 22.6 7.3 16.3 2.0 4.1 100
Kampala 19.3 28.3 32.6 11.5 4.3 3.1 0.5 0.4 100
Central1 4.2 18.7 32.5 21.1 6.5 13.0 1.6 2.5 100
Central2 1.0 10.9 26.6 24.4 8.2 20.3 2.5 6.2 100
Busoga 1.7 8.9 19.4 30.7 8.3 21.2 2.5 7.3 100
Bukedi 1.0 5.2 18.5 37.1 7.6 20.5 1.8 8.2 100
Elgon 1.8 3.8 19.8 39.0 7.0 18.7 2.4 7.3 100
Teso 0.9 3.7 15.2 35.6 5.6 18.2 1.6 19.3 100
Karamoja 0.4 3.7 6.1 8.3 3.1 7.0 3.6 67.8 100
Lango 0.7 4.7 13.4 40.8 6.2 20.9 2.1 11.3 100
Acholi 1.2 4.1 22.8 22.3 7.2 12.6 2.4 27.5 100
West Nile 0.6 2.4 16.4 36.1 7.4 22.1 2.3 12.7 100
Bunyoro 0.5 7.3 15.5 35.9 6.6 24.5 2.8 6.9 100
Tooro 1.2 5.3 18.2 43.8 7.0 19.7 2.2 2.8 100
Ankole 1.3 7.2 15.4 48.4 4.9 19.7 1.4 1.7 100
Kigezi 1.1 3.6 13.0 57.5 4.1 17.8 1.2 1.6 100
Uganda 2.6 9.3 21.0 32.5 6.6 17.8 2.0 8.3 100
Environmental Household Health 29
Figure 4.3 shows that urban dwellers are twice more likely to use improved toilet facilities compared to the rural dwellers (30% verses 18%). Households with no toilet facility are five times more likely to be in the rural areas compared to the urban areas.
Figure 4.3: Percent Distribution of Households using improved Toilet Facilities and place of residence
72 71 68
30
21 18 11 8 2
Improved Toilet Unimproved toilet No toilet
Urban Rural Uganda
The census sought to determine whether the toilet is used exclusively by the occupants of the living quarters being enumerated or whether it is shared with the occupants of other living quarters. Shared toilets increase the exposure to diseases that may be spread by poor or lack of sanitation. Figure 4.4 shows that shared toilets are predominant in the urban areas (47% compared to 12% in the rural areas) and it is highest in Kampala which is purely urban. Interesting to note is that in Karamoja region despite having the lowest percent of household with toilets, 1 in every 5 households share the facility.
Environmental Household Health 30
Figure 4.4: Percentage distribution of Households with shared Toilet Facility by Selected Characteristics
Sex of Household Head Male Headed 22 Female Headed 26 Residence Urban 47 Rural 12 Sub-Regions Central 31 Kampala 67 Central1 35 Central2 26 Busoga 21 Bukedi 15 Elgon (Bugishu/Sebei) 18 Teso 10 Karamoja 20 Lango 9 Acholi 14 West Nile 10 Bunyoro 17 Tooro 17 Ankole 18 Kigezi 10
4.3.2. Bathroom facilities As part of basic sanitation, proper management of waste water is vital to good health within households. Information on the type of bathrooms is used as a proxy indicator of liquid waste disposal.
4.3.2.1. Type of Bathroom Having no bathroom or having a bathroom with no drainage may pose serious public health issues. If wastewater leaks into structures harmful substances can because of the increased humidity that can promote environmental microorganisms to multiply and cause diseases and mold-associated allergies. Having no bathroom or having a bathroom with no drainage is highly linked to the welfare status of a household, the lower the welfare status the higher the percentage of such household and vise versa. This implies such household are exposed to health hazards. Table 4.6 shows no gender differences in what type of bathroom is used, differences are seen across regions Karamoja has the highest percentage of households with no bathroom or having a bathroom with no drainage (53%) followed by Acholi and Bunyoro regions at 48 percent.
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Table 4.6: Percentage distribution of households by residence, region, sex, and main type of bathroom used
TYPE OF BATHROOM MAINLY USED Outside Outside Inside, Inside, no built, built, no drainage drainage Make shift None Other Total drainage drainage provided provided provided provided Sex of Household Head
Male 5.7 2.1 31.6 18.2 26.1 14.6 1.7 100
Female 5.9 2.2 32.8 17.5 23.6 16.3 1.8 100
Region
Kampala 20.6 2.2 60.5 13.2 1.8 1.3 0.4 100
Central1 10.9 3.4 43.9 16.2 14 10.4 1.1 100
Central2 4.9 2.1 34.2 19.5 23.3 13.9 2 100
Busoga 3.6 1.9 37.9 25.9 18.3 10.7 1.7 100
Bukedi 4 1.5 33.8 23.4 28.3 7.9 1.1 100
Elgon 4.3 1.7 25.7 16.4 39.4 11.2 1.2 100
Teso 2.9 1.8 20.4 16.3 42.4 14.3 1.8 100
West Nile 3.5 2.2 41.8 22.7 11.9 16.2 1.8 100
Acholi 4.5 3.9 27.2 16.1 16.3 28.7 3.3 100
Lango 3.3 2.4 30.8 20 27.6 14.4 1.5 100
Karamoja 1.9 1.6 8.3 10.6 29.4 40.6 7.7 100
Toro 2.9 1.2 17.8 16.6 38.2 21.4 1.8 100
Ankole 4.4 1.3 19.5 13.9 46.5 13 1.4 100
Bunyoro 2.9 1.6 20.2 15.8 26.4 31 2.2 100
Kigezi 3.3 1.3 19.1 16.8 40.1 18.5 0.9 100
Wealth quintile
Lowest 1.3 1.7 15.2 17 31.1 30.4 3.2 100
Second 1.4 1.5 18.6 18.9 36.3 21.3 2 100
Middle 1.5 1.6 20.1 20.6 38.2 16.3 1.7 100
Fourth 5.0 2.6 34.9 21.2 24.8 10 1.4 100
Highest 16.1 2.9 60.5 13.7 4.2 2.2 0.5 100
Uganda 5.7 2.1 31.8 18.1 25.6 15 1.7 100
4.3.2.2. Use of Soap to bathe Taking a bath is important to ensure proper hygiene and use of soap for bathing is a good hygiene practice. Soap gives the following benefits when used to bath: it removes oil and dirt that can cause skin problems and even infections; and kills germs that can spread infections. The 2014 census therefore collected information from households about whether every member uses soap
Environmental Household Health 32
to bath. Table 4.7 shows that 95 percent of the households in Uganda use soap for bathing. Slight differentials are seen depending on the sex of the head and the place of residence. Wide variations are seen among regions with Karamoja region having the least percent of household members using soap for bathing (60%) compared to Kampala having 98 percent. The table also shows that the use of soap increases with the wealth status of the households from 81 percent in the lowest wealth quintile to 99 percent in the highest quintile. This is an indication that soap is one of these basic requirements that cannot be totally foregone even when there is scarcity of money.
Table 4.7: Distribution of households whose members use soap to bath by sex, residence, region, wealth status
Households whose members bath with soap Total Characteristic number of Number Percent households Sex of head Male 5,278,890 95.2 5,543,921 Female 1,637,604 93.0 1,760,149 Place of residence Urban 1,983,513 97.3 2,039,380 Rural 4,932,981 93.7 5,264,690 Region Kampala 407,864 98.4 414,406 Central1 1,013,120 97.0 1,044,133 Central2 810,311 96.4 840,403 Busoga 677,756 95.7 708,278 Bukedi 330,686 94.5 349,908 Elgon 350,121 96.2 364,033 Teso 301,698 93.9 321,241 West Nile 434,161 91.5 474,280 Acholi 262,121 89.0 294,598 Lango 394,781 94.7 416,820 Karamoja 97,320 59.5 163,464 Toro 519,319 95.2 545,758 Ankole 606,133 96.4 628,895 Bunyoro 418,144 96.7 432,214 Kigezi 292,959 95.9 305,639 Wealth quintile Lowest 1,050,359 81.2 1,293,030 Second 1,289,023 95.0 1,356,263 Middle 1,365,878 97.9 1,395,550 Fourth 1,388,055 97.9 1,418,181 Highest 1,766,225 99.2 1,780,462 Total 6,859,540 94.7 7,243,486
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Appendix table A9 shows that Kotido and Kaabong districts have only about half of the households that reported their members using soap for bathing (43% and 50% respectively).
4.3.3. Solid waste disposal Household waste management is recognized globally as a population based development indicatorxv. The NDP II has prioritized management of solid and recognized the need to strengthen production of statistics on waste management. The census therefore collected information on household solid waste disposal methods. Household solid waste comprises of garbage and rubbish (discarded items such as bottles, cans, clothing, compost, disposables, food packaging, food scraps, newspapers and magazines, and yard trimmings) and demolition or construction debris that originates from private homes or apartments. It may also contain household hazardous waste. It also includes household appliances, furniture, scrap metal, machinery, car parts and abandoned or junk vehicles. Disposal of solid waste and facilities have an extremely important impact on public health and on maintaining a safe environment. Research has shown that improper solid waste disposal activities have diverse effects ranging from health, environment, and human life and property. Rotten organic materials pose great public health risks, including serving as breeding grounds for disease vectors. Waste is typically disposed of without consideration for environmental and human health impacts, leading to its accumulation in cities, towns and uncontrolled dumpsites. Unattended waste lying around attracts flies, rats, and other creatures which creates unhygienic conditions and thereby leading to a rise in public health problems or spread of diseases. On the other hand people living close to a waste dump and those whose water supply get contaminated are at a high risk of being exposed to infections. Garbage is often burnt in residential areas to reduce volume and uncover metals. Burning creates thick smoke that contains carbon monoxide, soot and nitrogen oxides, all of which are hazardous to human health and degrade air quality. Table 4.8 shows that two thirds of the households in Uganda (66%) either dispose waste in the garden without burning or they burn it. Such households are exposed to the health risk of infections. According to the UN-Habitat health data, diarrhea and acute respiratory infections are significantly higher for children living in households where solid waste is dumped, or burned in the yard, compared to households in the same area that receive a regular waste collection service. In Uganda, diarrhea and acute respiratory infections have been ranking high among the causes of mortality among children under five years of age (HMIS data). Central 2 (82%) and Kigezi (81%) regions have the highest percentage of households that dispose garbage by burning or dumping. The practice is lower in the urban areas compared to the rural areas (52% vis-a-vis 72%), this may be attributed to the government investment in solid waste composting plants in the urban authorities (municipalities). The method of solid waste disposal does not vary by sex of household head.
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Table 4.8: Distribution of Households by Method of Solid Waste Disposal and Selected Characteristics
Local Dump not Garden Local Dump Supervised by Other Selected Characteristics without Burn Bury Supervised by Total Urban Arrangements burning Urban Authorities Authorities Sex of Household Head
Male Headed 43.9 22.7 8.3 6.8 11.1 7.2 100
Female Headed 42.8 23.0 7.5 8.5 10.3 8.1 100
Residence
Urban 20.3 31.9 6.3 19.7 8.9 12.9 100
Rural 52.6 19.2 8.8 2.4 11.6 5.3 100
Sub-Regions
Central 43.6 36.1 4.6 4.9 4.3 6.5 100
Kampala 2.6 18.6 2.4 41.0 6.8 28.7 100
Central1 39.3 39.1 4.3 4.7 3.9 8.7 100
Central2 48.9 32.5 4.8 5.2 4.7 3.8 100
Busoga 43.2 24.6 9.2 7.7 10.8 4.5 100
Bukedi 38.9 24.5 11.5 6.7 14.0 4.2 100
Elgon 57.7 15.5 9.0 4.6 10.0 3.2 100
Teso 45.2 18.4 11.3 4.3 15.9 4.8 100
Karamoja 37.4 25.6 5.3 2.3 13.5 15.9 100
Lango 37.1 20.0 14.6 3.2 17.1 8.0 100
Acholi 24.6 17.0 9.7 5.3 29.0 14.3 100
West Nile 33.0 16.0 15.8 5.5 22.7 7.0 100
Bunyoro 44.1 24.8 7.1 4.6 12.2 7.1 100
Toro 49.6 14.9 10.9 6.6 13.1 4.8 100
Ankole 67.1 10.4 6.0 5.3 7.1 4.1 100
Kigezi 73.8 7.1 7.3 2.9 6.1 2.8 100
Total 43.6 22.7 8.1 7.2 10.9 7.4 100
4.4. Cooking Arrangements
4.4.1. Fuel used for cooking Use of clean fuels for cooking improves the health of women through reduced exposure to smoke from wood fuels. This is because air pollution within the household is associated with poor health status, as use of unclean cooking fuel creates exposure to chronic or acute diseases. Table 4.9 also shows that nearly all households (95%) still use wood fuels (wood and charcoal) as a main source of fuel for cooking, which is a potential source of household air pollution that poses health risks particularly to those involved in cooking. Sustainable Development Goal 7 has a target to ensure universal access to affordable, reliable and modern energy services by 2030. In Uganda, the proportion of the population with access to
Environmental Household Health 35
electricity is very low with only 2 percent of the households using electricity as a main source of fuel for cooking. Furthermore, the proportion of the population with primary reliance on clean fuels and technology is also very low with only 3 percent of the households using clean fuels (either electricity or gas) as a main source of fuel for cooking. The use of clean fuels does not vary by gender as seen in table 4.9. The NDP II is cognizant of this very low use of electricity in Uganda and therefore aims to increase access to electricity and to promote the use of renewable energy.
Table 4.9: Distribution of Households by Main Source of Fuel for Cooking and Selected Characteristics
Characteristic Electricity Gas Paraffin- Charcoal Firewood Other Total Stove
Sex of Household Head
Male Headed 2.1 0.8 1.2 22.2 72.7 1.0 100
Female Headed 2.0 0.9 0.9 26.2 69.5 0.5 100
Residence
Urban 4.4 2.1 2.4 58.1 31.6 1.3 100
Rural 1.2 0.4 0.6 9.7 87.6 0.6 100
Sub-Regions
Central 2.7 0.9 1.5 36.6 57.4 0.9 100
Kampala 8.2 5.5 4.3 77.7 2.6 1.8 100
Central1 3.2 1.2 2 44 48.5 0.9 100
Central2 2.0 0.5 0.9 27.3 68.4 0.9 100
Busoga 1.6 0.4 0.5 20.1 76.8 0.6 100
Bukedi 1.1 0.4 0.6 11.2 86.3 0.5 100
Elgon 1.5 0.7 0.9 14 82.2 0.6 100
Teso 1.0 0.4 0.4 9.3 88.4 0.5 100
Karamoja 0.9 0.3 0.3 9 88.2 1.3 100
Lango 1.0 0.4 0.6 10.4 87 0.7 100
Acholi 0.9 0.4 0.7 17.3 80.2 0.5 100
West Nile 0.8 0.4 0.7 13.1 84.5 0.5 100
Bunyoro 1.5 0.4 0.6 14.8 82.2 0.5 100
Tooro 1.7 0.5 0.8 12.5 83.7 0.8 100
Ankole 1.9 0.5 1.1 13.8 81.4 1.3 100
Kigezi 1.7 0.4 0.5 9.5 86.9 1 100
Uganda 2.0 0.9 1.1 23.2 71.9 0.8 100
4.4.2. Type of kitchen Given that all households use wood fuel for cooking in Uganda, the location of the kitchen is key to understanding the extent of exposure to smoke especially for children and women. In addition, the likelihood of kitchen accidents. Short-term exposures (hours or days) to wood smoke can
Environmental Household Health 36
aggravate lung disease, causing asthmatic attacks and acute bronchitis, and may also increase susceptibility to respiratory infections. Wood smoke affects the quality of both indoor and outdoor air. The census collected information from households about the type of kitchen that is mainly used. Figure 4.5 shows that half of the households in Uganda have their kitchens built outside (51%) and a quarter of them use the open space outside. This implies 76 percent of the households are less exposed to smoke from wood fuels save for the women who do the cooking.
Figure 4.5: Percent Distribution of types of kitchen used by households
25 Open space 20 37
9 Make shift 10 7
51 Outside, built 58 34
7 Inside, no specific room 6 10
8 Inside, specific room 6 12
Uganda Rural Urban
Appendix table A6 shows that more than a third of the households in the following districts cook from inside the house with no specific room and are therefore more exposed to wood smoke: Lamwo, Gulu, Kitgum, Pader, Amuru, Agago, Nwoya and Omoro. These are all in Acholi region and this may attract further research. Well as the following districts have more than two thirds of the households that cook in the open space: Moroto, Kotido, Napak, Nakapiripirit, Figure 4.6 shows that two thirds of the households that use firewood as a main source of fuel for cooking use an outside built kitchen which reduces on exposure to smoke for other household members. Its observed that there are no major differentials in the type of kitchen by place of residence except for use of open space where the urban households are more likely than the rural households. This reaffirms that two thirds of the households in Uganda that use firewood are not 100 percent exposed to wood smoke and its direct health risks but destroy the environment through deforestation.
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Figure 4.6: Percent Distribution of households that use firewood by type of kitchen
60 61
21 18
10 10 6 5 4 5
Inside, specific room Inside, no specific Outside, built Make shift Open space room Urban Rural
4.5. Food Consumption
4.5.1. Meals taken by a household in a day The United Nations recognizes the human right to food as one of the fundamental rights. The right to food requires adequate food to be available and accessible. Adequacy refers to quantity, quality and appropriateness, taking into account cultural aspects as well as the physiology of the individual (e.g. sex, age and health). In the right to feed oneself in dignity, individuals are expected to meet their own needs, through their own efforts and using their own resources. To be able to do this, a person must live in conditions that allow him or her either to produce food or to buy it. This means that violating the right to food may impair the enjoyment of other human rights, such as the right to health, education or life, and vice versa. One of the interventions in the NDP II is to increase agricultural production and productivity with an aim to enhance consumption of diverse diets at household level. In addition, it aims to develop early warning systems to prevent and mitigate shocks affecting nutrition and food security. The goal of the Uganda Nutrition Action plan is to reduce malnutrition among women of reproductive age, infants and young children by promoting increased frequency of complementary meals at household level. The census collected information about the number of meals taken per day by members aged 5 years and above, and this analysis used this as a proxy for the consumption of adequate food. Figure 4.7 shows that only half (52%) of the households in Uganda usually take two meals in a day on average. Households that take one meal in a day are of concern as they may not be able
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to meet all the dietary requirements, these constitute 11 percent (792,707 households) which can lead to adverse health effects in such households.
Figure 4.7: Percentage distribution of households by average number of meals taken per day
4 or more meals 2% 1 meal 11%
3 meals 35%
2 meals 52%
1 meal 2 meals 3 meals 4 or more meals
Appendix table A 7 shows that the districts of Abim, Kotido, Napak, and Moroto have more than half of the households consuming only one meal in a day. In terms of numbers, Kampala and Wakiso district have the highest numbers of households (over 50,000 households). Map 4.4 shows that consumption of one meal a day is higher where poverty is high. This is in tandem with the point that poverty increases the chances of poor health so in addition to improved health, poverty should be dealt with.
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Map 4.4: Percent distribution of households whose members consume one meal a day
4.5.2. Sugar Intake Every cell in the human body needs sugar (glucose) to function. When the blood sugar levels drop too low, the body cells become starved for energy. Initially, that can cause minor symptoms, but if the blood sugar levels are not raised up soon, a person is at risk of serious complications such as; loss of consciousness, hormonal response, hypoglycemia unawareness, mood changes, muddled thinking, visual disturbances, sleep disturbances, sweaty skin, headache, seizures, rapid heartbeat and heart palpitations. These affect the ability to work and perform other daily functions.
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The 2014 census collected information from households whether every member recently (last one week prior to the census enumeration) consumed sugar at least once a day. Having sugar in the household is an indication that if knowledge of making recommended homemade fluids (mixture of salt and sugar) as Oral Rehydration Therapy (ORT) is available then it can be done for children with dehydration. Figure 4.8 shows that in Uganda not all households have all household members taking sugar for one reason or another, seven in every ten households have all members taking sugar at least once in a day. By place of residence, the urban dwellers were more likely to have consumed sugar compared to the rural dwellers (87% and 64% respectively). Appendix table A8 shows that the following districts have only around a third of the households with all members taking sugar at least once a day: Rubanda, Mitooma, Lamwo, Agago, kaabong, Kotido, Napak, Moroto.
Figure 4.8: Percentage of households with all members consuming sugar at least once a day
87.3
70.4 63.9
Urban Rural Uganda
4.5.3. Salt Intake Consumption of salt is essential to survival and good health. Lack of salt in the household in this analysis assumes that this household is either not eating salt or consumes low amounts to save on the available salt. This assumption is based on the factor that availability of salt in the household is an input into the measure of welfare status. A low salt intake is a risk factor for low blood sodium that is associated with higher mortalityxvi from cardiovascular events xvii especially among older people and those with chronic disease conditions. Common symptoms of low salt intake and therefore low blood sodium include: body weakness, fatigue or low energy, headache, nausea, vomiting, muscle cramps or spasms, confusion and irritability, which also affect the ability to work.
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Salt in Uganda is one of the main sources of iodine, 99 percent of the households consume iodized saltxviii. Continuous none availability of salt may lead to iodine deficiency and mental retardation in infants and children whose mothers were iodine deficient during pregnancy. The 2014 census collected information from households whether there was salt available in the household. Figure 4.9 shows that availability of salt in the household is almost universal with 96 percent of the households having it at a given moment in time, urban households being slightly more than the rural households (96% verse 94% respectively). Appendix table A8 shows that the following districts: Kotido (69%) and Moroto (76%) districts had the least percentage of households that had salt. Although salt is one of the cheap household basics, there are households that cannot afford it and may suffer the health risks associated with the non- consumption of salt.
Figure 4.9: Percentage of households with salt available
95.7
94.3
93.7
Urban Rural Uganda
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4.6. Child warmth
When the body temperature drops below 98.6˚F (37˚C), a person may experience: shivering, an increased heart rate, slight decrease in coordination and an increased urge to urinate. When the body temperature further drops to below 71.6˚F (22˚C), it can result in muscles becoming rigid, blood pressure becoming extremely low or even absent, heart and breathing rates decreasing, and it can ultimately lead to death. The effects of cold weather on health are predictable and mostly preventable. Knowing that the wee hours of the day are usually much colder than the day and worse during the wet season, it is important that every child is kept warm during sleep. This will maintain good health and avoid cold related illnesses that can affect their productivity in school and subsequently their future wellbeing. The 2014 census collected information from households about whether every child (below 18 years of age) has a separate blanket. Figure 4.10 shows that less than half of the households (47%) in Uganda do not have a separate blanket for each child, the rest either share or do not have at all. The urban households are more likely than the rural households to have a separate blanket for each child (59% and 43% respectively).
Figure 4.10: Percentage of households with every Child having a separate blanket
58.6
47.2 42.8
Urban Rural Uganda
Note: Excludes children aged one year or less Map 4.5 shows that the semi-arid districts have higher percentage of households where each child uses a separate blanket compared to the other regions. that are generally colder. This would be a cultural issue about sharing blankets.
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Map 4.5: Percent distribution of households with every Child having a separate blanket.
4.7. Use of shoes
Shoes protect the feet from injuries, germs and parasites as well as avoiding the possibility of contracting hookworms and Jiggers. These parasites enter the skin by burrowing under the surface when they come into contact with the feet. Infestation with such parasites can deteriorate the health status and affect general performance at work, school, and elsewhere. The 2014 census sought to establish the number of households with all members having at least one pair of shoes. Given the atmosphere in the urban areas with most people walking in shoes its expected and shown in figure 4.11 that there are more households in the urban areas with all members having a pair of shoes compared to the rural areas (89% verse 61%) making the national average at 69 percent.
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Figure 4.11: Percentage of households with every member having at least one pair of shoes
88.9
69.1 61.4
Urban Rural Uganda
4.8. Mosquito nets
Malaria is one of the leading causes of morbidity and mortality in Uganda. The Government of Uganda and Development Partners have injected large sums of money into procurement and distribution of Long Lasting Insecticide Treated Nets (LLIN) as a means of reducing the spread of malaria. The 2014 census therefore collected information about the ownership of any mosquito net in the household and how the net was obtained. The census results show that ownership of mosquito nets by households is almost universal (93%). Figure 4.12 demonstrates almost all households that have nets obtained them for free from government, Non-Government Organizations or from a friend or relative. The exception is Kampala city and other urban areas which have a sizeable percentage of households that bought the nets.
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Figure 4.12: Distribution of Households by Ownership of Mosquito Nets and source of nets by Residence and Sub-Region
0 10 20 30 40 50 60 70 80 90 100
Residence Urban Rural Sub-Regions Kampala Central1 Central2 Busoga Bukedi Elgon (Bugishu/Sebei) Teso Karamoja Lango Acholi West Nile Bunyoro Tooro Ankole Kigezi
Uganda
Own Nets Nets given free
Map 4.3 shows the distribution of households that own a mosquito net, it can be seen that districts with the lowest percentage of households that own nets are in or around the Lake Victoria specifically: Kalangala (79%), Mayuge (79%), Bugiri (83%) and Buvuma (83%) including Amudat and Kaliro districts. This can be attributed to the fact that many of the people living in these areas only have temporary homes that they use seasonally, when conducting business on the lake. Important to note that ownership does not tantamount to usage, There is need to further establish the usage visa vie malaria incidence and prevalence in these districts to understand the efficiency and effectiveness of promoting use of nets to prevent malaria.
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Map 4.6: Percent distribution of households that own a mosquito net
4.9. Social problems affecting communities
A social problem is an issue that influences a sizeable number of individuals within a society. Focus Group discussions were held with opinion leaders, Local Council Committee members and elders at the village level to seek for their views and perceptions about selected issues that affect their communities. Figure 4.13 shows that in Uganda, around four in every ten village communities cited the following health related issues as major problems that affect them: no hospitals, poverty and lack of water within their villages.
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The HSDP recognizes that addressing social determinants of health has been shown to be an effective way of increasing equity of access and to achieve universal health care. These results are thus useful in understand the social concerns of each community so they can be dealt with alongside other health interventions.
Figure 4.13: Percent Distribution of LCIs by health related social problems affecting residents
46
41
35
9 7 5
Poor Sanitation No Hospitals Poverty Lack Of Water Famine Drunkardness
4.10. Distance to health facilities
One of the key health sector Performance indicators for measuring contribution towards the production of a healthy human capital for wealth creation through provision of equitable, safe and sustainable health services is “Population living within 5km of a health facility”. Table 4.10 shows that 79 percent of the households are within a 5 kilometre distance to a health facility which is an improvement from 73 percent observed in the 2002 census. This is still below the target of the HSDP of 85 percent to be achieved in 2019/20. In terms of increasing access, the regions of Teso, Acholi, Lango, karamoja, Toro and Bunyoro can be prioritized given that they have the least percentage (below national level) of households within a 5 km distance to a health facility.
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Table 4.10: Distribution of Households within a 5 Kilometer distance to a health facility by Selected Characteristics
Public Facility Private facility Any Facility
Number % Number % Number %
Sex of Household Head
Male 3,707,305 66.9 3,295,998 59.5 4,327,418 78.1
Female 1,230,699 70.0 1,123,656 63.9 1,427,192 81.1
Place of Residence
Urban 1,718,074 84.3 1,771,716 86.9 1,912,281 93.8
Rural 3,219,930 61.2 2,647,938 50.3 3,842,329 73.0
Region
Kampala 339,068 81.9 384,594 92.8 396,629 95.7
Central 1 768,325 73.6 829,129 79.5 917,486 87.9
Central 2 539,427 64.2 541,913 64.5 657,825 78.3
Busoga 503,835 71.2 466,564 65.9 574,209 81.1
Bukedi 268,439 76.8 215,105 61.5 295,141 84.3
Elgon 288,830 79.4 248,093 68.2 318,017 87.4
Teso 185,138 57.7 144,521 45.0 218,059 67.9
West Nile 333,868 70.5 222,175 46.9 371,541 78.3
Acholi 186,162 63.2 114,612 38.9 203,257 69.0
Lango 219,713 52.8 166,175 39.9 274,576 65.9
Karamoja 90,934 55.7 51,272 31.4 105,042 64.3
Toro 320,430 58.8 277,183 50.8 377,610 69.2
Ankole 421,660 67.1 361,406 57.5 488,604 77.7
Bunyoro 243,722 56.4 225,639 52.2 303,084 70.1
Kigezi 228,453 74.9 171,273 56.1 253,530 83.0
Uganda 4,938,004 67.7 4,419,654 60.5 5,754,610 78.8
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CHAPTER POPULATION HEALTH STATUS AND FIVE: OUTCOMES
Key Findings • Life expectancy at birth was 63.7 for Uganda as a whole and for males was 62.8 years and
64.5 years for females • Between 1991 and 2014, Infant and Under Five Mortality rates declined by more than half, dropping from 122 to 50 deaths per 1000 live births and from 203 to 74 deaths per 1,000
live births respectively • 236 male deaths compared to 189 female deaths per 1,000 population was observed among persons aged between 15 and 60 years
• The maternal mortality ratio for the 12-month period preceding the census is 380 deaths per 100,000 live births • Close to 9 in 10 persons died because of a disease
5.1. Trend/Evolution of life expectancy at birth between 1969 and 2014 Life expectancy is a measure that is often used to gauge the overall health of a community. The indicator is measured as “Life expectancy at birth”, which is an estimate of the average number of years that a newborn is expected to live, subject to the population’s mortality risks at the time of birth. It gives a summary measure of the mortality experience of the population at all ages. This is an important indicator of the health and socio-economic status of the population that is being monitored in the NDP, and it is a key element of the “long and healthy” dimension of Human Development Index (HDI). Figure 5.1 shows that, for Uganda the life expectancy at birth in 2014 was 63.7 years. For males was 62.8 years and 64.5 years for females. This means that males and females born in Uganda now and subjected during his/her entire life to the current levels of mortality at the different ages would expect to live for 62.8 years and 64.5 years respectively. Between 2002 and 2014, males and females gained with slightly more 13 years in life expectancy at birth, which could be attributed to improvement in childhood mortality rates. The current achievement of life expectancy at birth, based on the 2014 census results show good progress to the extent that overall, the NDP’s public health target of 60 years has been attained. According to the literature, females live longer than males for both biological and behavioural reasons. In terms of biological reasons, women possess genes that expose them to a longer life than men. In terms of behaviour, women’s pay more attention than men to their health, seek care
Population Health Status and Outcomes 50
when they are sick more frequently than men, are less prone to risky behaviour such as smoking, alcohol drinking, drug consumption and are less at risk of injuries and violent deaths such as traffic accidents and exposure to occupational risks, etc.
Figure 5.1: Life Expectancy at Birth by Census Year 1969- 2014
70.0 62.8 64.5 63.7 60.0 52.0 50.5 48.1 48.8 50.4 50.0 46.0 47.0 46.5 45.7
40.0
30.0
20.0
Life Life Expectancyat birth 10.0
0.0 1969 1991 2002 2014
Male Female Total
Figure 5.2 clearly shows that irrespective of age, females generally live longer than the males and the differences are minimal after the age of 70 years. Note that life expectancy declines with age; as people get older, they have fewer years ahead of them. The exception is between ages 0 (life expectancy at birth) and 1; life expectancy actually rises for those children that reach one year of age.
Figure 5.2: Life Expectancy as of Census 2014
80 70 60 50 40 30
20 Expected years of life of years Expected 10 0 0 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 Current age Female Male
Map 5.1 shows that life expectancy among women varies by district. Appendix table A10 shows that the following districts have the highest female life expectancy of 72 years and above:
Population Health Status and Outcomes 51
Nakapiripirit, Kampala, Kaabong, Bushenyi, Kisoro, Amudat and Napak. The following districts have the lowest life expectancy among women i.e. less than 59 years: Zombo, Lyantonde, Rubirizi, Ssembabule and Rukungiri, these should be of policy interest.
Map 5.1: Female Life Expectancy at Birth as of Census 2014
Map 5.1 and 5.2 shows that life expectancy is not obviously high or low for both sex in a district. For instance, male life expectancy is lowest (below 55 years) in the following districts: Rakai, Lyantonde, Kyegegwa, Lwengo, Buhweju, Bullisa, Moyo and Kyotera. Of these Lyantonde has the least for both male and female which should be an issue of concern. On the other hand, Napak district has the highest life expectancy both among males and females. The good practices in Napak should be emulated elsewhere to prolong life.
Population Health Status and Outcomes 52
Map 5.2: Male Life Expectancy at Birth as of Census 2014
5.2. The mortality pattern in Uganda Mortality refers to deaths that occur within a population. Death is a fact of life with many social, emotional and biological implications. The probability of dying depends on a number of factors which can be characterized as demographic, social and economic factors. Understanding the country’s mortality levels, patterns and trends is therefore an important part of any health service delivery system. Information on mortality provide insights that are necessary for public health policy or programme formulation, implementation and evaluation. It also helps in informing insurance related policies and understanding the quality of human capital in the country.
Population Health Status and Outcomes 53
The 2014 National population and Housing Census (NPHC) asked questions about deaths in the household during the last 12 months preceding the census date, as well as the causes of the death as perceived within the household.
5.2.1. Mortality by Specific Age Groups The probability of dying is the chance that a person of that age will die before his or her next birthday. It analyzes patterns in mortality rates of a population that can be observed over time. Figure 5.3 shows that death in Uganda are higher among children age below 5 years with males having a higher probability of dying. Thereafter, mortality reduces and gradually increases and shots up from 60 years with males having a higher probability of dying than females. The curve follows approximately a “U” shape for high mortality countries, meaning that mortality is high during childhood and old-age with similar levels and lower during the adult ages. This suggests the need for a health system response, based on services that are tailored to address health issues among children under the age of five and the elderly.
Figure 5.3: Probability of dying by Age group and Sex
0.4
0.35
0.3
0.25
0.2
0.15 Probability of dying of Probability 0.1
0.05
0 0 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 Age
Male Female
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5.2.2. Childhood mortality Child mortality is a core indicator of child health and well-being. The Sustainable Development Goal 3 (target 3.2) renewed commitment to the health of the world’s children by 2030, end preventable deaths of newborns and children under five years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 deaths per 1,000 live births and under-five mortality to at least as low as 25 deaths per 1,000 live births”. The Infant Mortality Rate (IMR) gives the probability that a newly born child will not survive to the first birthday, while the Under -five Mortality Rate is the probability that a child born will not survive to the fifth birthday. Figure 5.4 shows the questions that were asked to determine child mortality.
Figure 5.4: Census 2014 questions
Table 5.1 presents data on deaths among infants and children under – five years per 1,000 live births from 1969 to 2014.The results show the probability of dying before the first birthday (IMR) in 2014 as 50 per 1,000 live births. It is higher for boys (54‰) than for girls (46%). Infant and Under Five Mortality rates declined by more than half between 1991 and 2014, from 122 to 50 deaths per 1000 live births and from 203 to 74 deaths per 1,000 live births respectively. This is marked progress, but more efforts are still required to achieve the national target of 44 (for infants) and 55 (for under five) deaths per 1,000 live births as set in the current NDP; as well as SDG target number 3.2.
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Table 5.1: Childhood mortality 1969-2014
Infant Mortality Rate Under Five Mortality Rate
Census Year Male Female Total Male Female Total 1969 129 110 118 211 189 198
1991 131 112 122 216 194 203
2002 91 84 87 160 152 156
2014 54 46 50 79 69 74
Map 5.3 shows the under-five mortality rates variation by district. The districts that have the highest under five mortality rate of over 120 deaths per 1,000 live births include: Zombo, Bullisa, Kyegegwa, kamwenge, Rubirizi, Buhweju, Lyantonde and Rakai while Kitgum, Napak and Nwoya districts had the lowest rates of less than 20 deaths per 1,000 live births. Districts with high mortality require more targeted interventions to reduce child death while those with low mortality can be studied to pick lessons about the drivers of reducing mortality.
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Map 5.3: Under five Mortality by district
Similarly, map 5.4 shows that the rate at which children die before they reach their first birthday varies by district. The same districts with high under five mortality have a high infant mortality rate. This further illustrates that children die early in those districts and the factors behind this sky-high infant mortality need to be addressed as this is a critical area of focus for maternal, newborn and child health service delivery.
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Map 5.4: Infant Mortality by district
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5.2.3. Adult Mortality
Figure 5.5: The set of questions asked and from which adult and pregnancy related death are computed
Understanding adult mortality among these economically and biologically productive population sub-group is important to give meaningful health interventions to reduce mortality and ill-health. This must therefore be informed by the magnitude, the spatial distribution and cause of illness and death leading to proper economic and social planning in the health sector. Adult mortality refers to death of persons who are aged between 15 and 60 years, it is measured as a rate of number of deaths per 1,000 population in that age group. In addition to life expectancies at selected ages, the conventional measure of adult mortality which is computed as a probability of death 45 q 15 (that is, the conditional probability of death by age 60 given survival to age 15) is preferred and is more precise. The probability of dying between ages 15 and 60 among males is 25 percent higher than that of females in Uganda – 236 male deaths compared to 189 female deaths per 1,000 population was observed among persons age between 15 and 60 years in Uganda. Thus approximately 1 in every 4 males die within a 12-month period. This rate is too high, the likely causes of death that require policy concern are illustrated in section 6.3 of this report. Map 5.5 shows that male adult mortality is highest in Moyo (318 deaths) and Bullisa (299 deaths) district. It is also clustered in some districts of mid-western to south central region, West Nile, Lango and parts of the eastern region.
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Map 5.5: Male Adult Mortality by district
Map 5.6 shows that mortality among the females varies by district. Comparing with map 5.5, some districts have high mortality among both the male and female while in others, gender differentials exist and the number of deaths are at extremes. For instance, Moroto, Pader, Omoro, Agago districts had very high mortality among women and a very low mortality among men. A likely explanation of this difference is gender inequality, and low educational attainment among women that may affect females’ access to health care services. In addition, the disadvantaged and/or vulnerability position of women in the family and in society may also affect living conditions that reduce their life expectancy. There is a need to further investigate the causes of death through
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in-depth health studies and qualitative research so that interventions can be targeted by gender to avert death and maintain a healthy human capital.
Map 5.6: Female Adult Mortality by district
5.2.4. Older Persons Mortality The National policy for older persons defines older persons as women and men aged 60 years and above. Therefore, this report captures mortality among the older persons through life expectancy at age 60 (e60). Given the current mortality levels, a person who reaches the age of 60 in Uganda would expect to live for about 17 more years for males and 22 for females. Comparing with the 2002 census, life expectancy at age 60 has remained the same among males and improved a little among the females. This modest progress can be attributed to factors in life such as gender, genetics, access to health care, hygiene, diet and nutrition, exercise, lifestyle, and crime rates. There is therefore need for effective execution of population health management
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initiatives that are targeted for improving the quality of life (health or living standard) of the older persons as highlighted in the National Policy for Older persons; including strengthening strategies for prevention and treatment of illnesses among elderly persons.
Figure 5.6: Life expectancy at age 60 (e60) by sex
21.7
18.9 17.2 17.3
Census 2002 Census 2014
Male Female
5.2.5. Maternal Mortality Pregnancy-related mortality is regarded as a key indicator of a population’s health and of a society’s development. Information on maternal mortality serves the needs of the health sector in terms of aiding the formulation and execution of healthcare interventions that are aimed at reducing deaths both during pregnancy and deaths after termination of pregnancy, such as increasing the coverage of deliveries attended to by skilled health personnel; the number of health facilities providing neonatal, child and maternal health services to the lowest health facilities; and expansion of Emergency Obstetric Care (EMOC) coverage. Indeed, a number of global health initiatives and the national health sector development agenda prioritizes Reproductive, Maternal, Neo-natal and Child health care service delivery to enhance maternal as well as child health outcomes. Results in Table 5.1 indicate that the rate of mortality associated with pregnancy and childbearing is 0.66 maternal deaths per 1,000 woman-years of exposure. The estimated age-specific mortality rate is highest among women aged 45-49 (1.42) which may be associated with high risk factors due to “too late” births and lowest among women aged 15-19 (0.38). Maternal deaths account for 16 percent of all deaths among women aged 15-49 years during the 12-month period preceding the census. The maternal mortality ratio (MMR) is expressed per 100,000 live births in order to emphasize the obstetrical risk of pregnancy and childbearing. The estimate of the maternal mortality ratio for the
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12-month period preceding the census is 380 deaths per 100,000 live births; that is there are over 3 maternal deaths for every 1,000 births in Uganda. This is consistent with the 2016 UDHS result of 368 deaths per 100,000 live births which is high and requires strategic interventions.
Table 5.2: Maternal Mortality
Maternal Mortality Age Number of Deaths Maternal Mortality Rate Percentage of female Ratio (per 100,000 live group due to Maternal Cases (per 1,000 women) deaths that are maternal births) 15-19 764 305 0.38 10.6
20-24 848 200 0.50 18.7
25-29 872 271 0.66 22.4
30-34 801 374 0.77 16.2
35-39 759 634 0.94 23.2
40-44 581 1,183 0.89 10.1
45-49 660 6,111 1.42 18.2
Total 5,285 380 0.66 15.9
Table 5.2 shows that maternal mortality is generally high and varies across regions. The Karamoja region has the highest maternal mortality rate of 588 deaths per 100,000 live births, this is followed by Kigezi and Central 1 region that have over 500 deaths per 100,000 live birth. This calls for a need to further investigate the causes of this high maternal mortality in order to guide region- specific interventions aimed at maternal mortality reduction.
Table 5.3: Pregnancy Related Mortality by region
Percentage of female Lifetime Risk of Maternal Mortality Maternal Mortality deaths that are Maternal Death Ratio (per 100,000 live Rate (per 1,000 maternal (per 100 women) births) women) Kampala 13.7 1.7 0.479 394 Central1 13.9 2.8 0.795 505 Central2 16.4 2.6 0.74 410 Busoga 17.2 2.6 0.732 379 Bukedi 18.2 1.6 0.443 227 Elgon 16.9 2.1 0.595 349 Teso 19.9 1.4 0.401 208 Karamoja 21 3.5 1.007 588 Lango 11.4 1.7 0.484 279 Acholi 16.9 3.1 0.892 466 West Nile 10.5 1.9 0.545 304 Bunyoro 16.8 2.2 0.642 316 Toro 16.5 2.0 0.564 296 Ankole 19.8 2.7 0.766 489 Kigezi 24.8 2.8 0.801 541
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Figure 5.7 shows the proportion of female adult death by age and timing of death. Of the women that died during pregnancy, the highest proportion was aged 25 to 29 years. On the other hand, of those who died during child birth or in the 6 weeks period after delivery the highest proportion were aged 35 to 39 and 45 to 49 years. This information is useful for the health sector to target appropriate interventions for addressing pregnancy and birth related deaths.
Figure 5.7: Proportion of adult female deaths due to maternal causes
12
10
8
6
4
percent percent offemale death 2
0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age at death Pregnancy Childbirth Six weeks
5.3. Causes of death
Understanding the cause of death is important to inform the planning process to reduce mortality. It is important to note that the causes of death in this report are not clinically established sources, but captured as reported by the census respondents.
Results in Figure 5.8 show that close to 9 in 10 persons died because of a disease, the specific diseases can be obtained from the DHIS so that interventions can be targeted accordingly. The next notable cause of death is accident, which accounts for 8% of the deaths reported. Therefore, in addition to specific disease prevention and treatment interventions, it is important that through inter-sectoral coordination, accidents (e.g. road accidents) are consistently put in checks through effective accident control measures.
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Figure 5.8: Distribution of reported causes of death
Violence Witchcraft 2% 3% Accident 8%
Disease 87% Gender differentials exist in the reported causes of death as shown in figure 5.9 to 5.12. Results in Figure 5.9 show that more females than males were reported to have died because of a disease. Much fewer males in the age group of 20 to 29 are reported to have died from a disease, implying there are other likely reasons for male mortality in this age group.
Figure 5.9: Age- Sex Distribution of death due to disease
100 90 80 70 60 50
40 Percentage 30 20 10 0 0-4 5-9 10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84 85+ Age at death
Female Male
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Figure 5.10 shows that generally more males than females die from accidents in and out of home, most especially in the age group of 20 to 29 years. This points to the need to address particularly the challenge of road traffic accidents.
Figure 5.10: Age- sex Distribution of death due to accidents
25
20
15
Percentage 10
5
0 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Age at death Female Male
Figure 5.11 shows that the males were also more likely to die from violence compared to the female and the most at risk is 25 to 29 years for both females and males. This points to the need to further administrative data to understand the causes of violence and how it can be curbed or how the victims can be supported.
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Figure 5.11: Age- Sex Distribution of death due to violence
7
6
5
4
3 Percentage 2
1
0 0-4 5-9 10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84 85+ Age at death
Female Male
Witchcraft was mentioned as a cause of death in Uganda. Figure 5.12 shows that more women than men at the age of 25 to 29 years were reported to have died from witchcraft, and from the age of 40 years and above, more men than women were reported to have died from witchcraft.
Figure 5.12: Age- sex Distribution of death due to witchcraft
8
7
6
5
4
Percentage 3
2
1
0 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Age at death
Female Male
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CHAPTER POLICY FRAMEWORK, CONCLUSIONS SIX: AND POLICY IMPLICATIONS
6.1. Policy frameworks Uganda’s development framework and the economy at large is guided by the National Development Plan. The country is now implementing her second National Development Plan (NDP II) which is designed to propel the economy towards middle income status by 2020 in line with the Vision 2040. The NDP is implemented through Sector Investment Plans (SIPs), Local Government Development Plans (LGDPs), Annual work plans and Budgets of Ministries, Departments and Agencies (MDAs). The NDP II also seeks to leverage the International and Regional Frameworks such as Africa Agenda 2063 and the Post 2015 Development Agenda to exploit growth opportunities. Specifically, in the health sector, the guiding framework for the sector’s development is the National Health Policy (NHP), which has been designed to attain the goal of a good health standard for all Ugandans in order to promote health and productive lives. The NHP is being operationalized through the Health Sector Development Plan (HSDP 2015/16-2019/20). The government has currently prioritized achievement of Universal Health Coverage (UHC), as stipulated in the HSDP with the overall goal of accelerating movement towards Universal Health Coverage (UHC), and this goals is well aligned to the third SDG.
6.2. Conclusion The main purpose of a census is to know the number of people living in a given place. The fundamental purpose of the population census is to provide the facts essential to governmental policymaking, planning and administration. Availability of census data can assist local communities in assessing their conditions of living and give them the information they need to participate and advocate in the development of programmes and policies affecting their communities, such as those impacting health systems, models of economic production, environmental management and social organization. In addition, the development of indicators relevant to the local population and the measurement of such indicators in the data collection process can be used to monitor the human development of local populations. The census data in general are not as complete and reliable as data obtained with a specialized demographic household survey, but census data has two advantages. First, there are no sampling concerns, which sometimes may result in serious problems of reliability in survey information. The second advantage is that there is sizeable knowledge and experience in the evaluation and adjustment of data on deaths by age and sex to address these problems. Some results suggest the expansion of conventional health services and infrastructure to reach marginalized populations, especially those living in hard-to-reach and remote areas. Policies
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directed to further reduce the fertility rate may also have important effects on under-five mortality. These results also call for gender and age considerations in the formulation of health policies, as well as the importance of interventions that aim to change behaviours towards healthier lifestyles, especially among males.
6.3. Policy Implications The findings from the 2014 census have ramifications for policy and public health programming, particularly pertaining to formulation, implementation, and reviews of different policies or programmes. The main issues that health policy or public health interventions should address, or put more emphasis on, based on the census results are discussed below. The areas policy interventions are presented following key findings under each chapter of this health thematic report. Given the sky-high high fertility rate, there is need to fast track strategies or initiatives for accelerating fertility decline. Stimulating an accelerated fertility decline is essential, given the country’s fertility pattern that has remained high and almost flat. Rapid fertility decline is a requisite for achievement of the target set in the HSDP as well as global health SDG, and for fostering the demographic dividend for the country. Family planning and other interventions focusing on fertility decline should place more attention on rural areas, the non or poorly educated women, and sub-regions with the highest fertility rates. Increasing access to family planning can be achieved through community- based distribution of contraception. Pertaining to birth certification, it is important to revitalize efforts to strengthen or fully operationalize formal birth registration initiatives in the entire country to ensure effective planning at different levels and improve public health programming. The collaboration between Ministry of Health or health facilities and the National Identification and Registration Authority (NIRA) need to be strengthened to ensure birth registration is done at facility level, for deliveries that take place at health facilities. This can involve linking facility based birth records that are captured in maternity related Health Management Information System (HMIS) to NIRA birth declaration. For births that occur in the community (outside health facilities), registration and notification can be rolled out at lower levels such as parishes or villages, and later on submitted to sub-county or division headquarters. To address challenges of early marriage and teenage pregnancy and births, implementation of interventions related to sexual and reproductive health education that have been outlined in the HSDP must be fast tracked. Health education should be heightened both in the community and schools, which requires close collaboration with the Ministry of Education and Sports, as well as district education and health offices. Health promotion and information dissemination in the community and schools are vital for curbing high risk births such as; too early and too late births. Also, targeted interventions to address socio-cultural factors leading to women having too many children are critical, especially the most affected sub-regions of Busoga, Teso, and Bukedi.
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Implement and strengthen inter-sectoral collaboration and strategies to address social determinants of health in order to curb different sorts of health risks that the population is faced with due to prevailing socio-economic and environmental conditions. Some of the identified conditions that present critical health risks include; poor housing conditions (including overcrowding), inadequate access to safe or clean water, use of unclean fuel (energy) for cooking, insufficient food (unavailability/inaccessibility), and non-use or unavailability of mosquito nets. Addressing these socio-economic and environmental conditions through effective multi-sectoral interventions (e.g. targeted investments in girl’s education – keeping the girl child in school) is also critical for tackling challenges related to; high fertility level, teen age pregnancy and early child bearing, high risk births, and health promotion and prevention. Other critical interventions to address socio-economic and environmental determinants of health include public investments in; descent housing facilities (e.g. through a national housing policy), safe and clean water supply in all parts of the country, food security, road traffic accident control programmes, promotion of healthy habits, and avoidance of risky lifestyle or behaviours among others.
Fast track implementation strategies for UHC related interventions as prescribed in the HSDP, to ensure accelerated progress and/or improvement in health outcomes such as; fertility, disease burden and morbidity, life expectancy, infant and child mortality, and maternal mortality. Effective delivery of Reproductive, Maternal, Neonatal and Child healthcare (RMNCH) services is critical in addressing most of the health risks and burden among the vulnerable group of children and women, while paying heed to rural areas and sub-regions or districts with poorer RMNCH outcomes. Furthermore, given that the main cause of death is disease, special attention should be paid to health promotion and disease prevention measures; and meaningful investments in healthcare infrastructure (including medical supplies) is important for improvement of care and treatment services for the section of the population that require the services due to illnesses. Taking into consideration that policy interventions should be evidence based, it is important to note that the issues highlighted below provide areas of proposed or further research that are useful for generating comprehensive evidence to inform policy processes: 1) Analysis of the main determinants of the geographical distribution of infant and child mortality i.e. Why is it very high in some districts, based on a suitable and robust modeling approach. 2) Analysis of the main differentials and covariates of early-age mortality, in particular those indicators of fertility and family composition: this study can be conducted with data from the 2014 Census, ideally using a multi-level approach that uses aggregate as well as individual level variables. 3) Identification of the main determinants of adult mortality: this includes an in-depth analysis of adult mortality sex differentials especially within the same districts.
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References A Foldspang, S Mommsen, G W Lam, and L Elving. 1992 Dec. Parity as a correlate of adult female urinary incontinence prevalence. Journal of Epidemiology and Community Health.; 46(6): 595–600. PMCID: PMC1059675.
Heliövaara M, Aromaa A. Parity and obesity. Journal of Epidemiology & Community Health 1981;35:197-199.
International Monetary Fund – IMF. (2004). Health and development: Why investing in health is critical for achieving economic development goals. International Monetary Fund, Washington DC, USA.
Kyle Steenland, Cathy Lally and Michael Thun. Nov., 1996. Parity and Coronary Heart Disease among Women in the American Cancer Society CPS II Population. Epidemiology Vol. 7, No. 6, pp. 641-643
Lijun Shen, Jing Wu, Guiqiang Xu, Lulu Song, Siyi Yang, Jing Yuan, Yuan Liang, and Youjie Wanga, 2015 Nov 26. Parity and Risk of Coronary Heart Disease in Middle-aged and Older Chinese Women. doi: 10.1038/srep16834 PMCID: PMC4660373
Lechner, L.; Bolman, C.; van Dalen, A. 10 October 2006. "Definite involuntary childlessness: associations between coping, social support and psychological distress". Human Reproduction. 22 (1): 288–294. PMID 16920722. doi:10.1093/humrep/del327
Martin J. O'Donnell, MB, PhD; Salim Yusuf, DPhil, FRCPC, FRSC; Andrew Mente, PhD; et al Urinary Sodium and Potassium Excretion and Risk of Cardiovascular Events
Medalia C and V W Chang. 2011. ‘Gender equality, development, and cross-national sex gaps in life expectancy’, International Journal of Comparative Sociology 52 (5) pp. 371-389.
2Ministry of Health. September 2015. Health Sector Development plan for 2015/16 -2019/20
Monroy De Velasco A. December 1982. Consequences of early childbearing. Draper Fund Rep.;(11):26-7.
Naomi J. Spence. The Long-Term Consequences of Childbearing: Physical and Psychological Well- Being of Mothers in Later Life.
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National Planning Authority (NPA). June 2015. Second National Development Plan (NDPII) 2015/16 – 2019/20
Taylor RS1, Ashton KE, Moxham T, Hooper L, Ebrahim S. Reduced dietary salt for the prevention of cardiovascular disease: a meta-analysis of randomized controlled trials (Cochrane review).
Tylee A, Haller DM, Graham T, Churchill R et al Youth-friendly primary-care services: how are we doing and what more needs to be done. The Lancet, 2007, 369.
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Uganda Bureau of Statistics (UBOS) and ICF. 2012. Uganda Demographic and Health Survey 2011: Main Report. Kampala, Uganda: UBOS, and Rockville, Maryland, USA: UBOS and ICF.
Uganda Bureau of Statistics (UBOS) and ICF. 2017. Uganda Demographic and Health Survey 2016: Key Indicators Report. Kampala, Uganda: UBOS, and Rockville, Maryland, USA: UBOS and ICF.
Uganda Bureau of Statistics. September 2017. Uganda National Household Survey 2016/17. Kampala, Uganda
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World Health Organization. Making health services adolescent friendly. Developing national quality standards for adolescent friendly health services.
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Glossary of terms and definitions
Child mortality: The probability of a child dying between their first and fifth birthday.
Child mortality rate: The number of children that die between 1 and 4 years of age divided by the number of children alive at age 1, multiplied by 1,000.
Infant mortality: Deaths of children before attaining exact age 1.
Infant mortality rate: The number of deaths of infants aged under one year per 1,000 live births (and sometimes referred to as the probability of death from birth to age 1).
Life expectancy: The average number of additional years that a person could expect to live if current mortality levels were to continue for the rest of that person’s life.
Life expectancy at birth: The average number of years that a newborn baby is expected to live if the mortality conditions of the year corresponding to the life table remain constant.
Under-five mortality rate (U5MR): This is an approximation of the probability of dying before the age of five. It is the number of children who die before reaching five years of age (numerator), divided by the total number of live births in a given one-year period (denominator), multiplied by 1,000.
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APPENDICES
Table A.1: Total Fertility Rate and possession of a birth certificate by district and place of residence
Total Fertility Rate Has Birth Certificate
District Urban Rural Uganda Number of Percent of Total Number registered under 5 who of children children are registered below 5 years Central Region
Buikwe 5.2 6.1 5.4 24,318 34.5 70,422
Bukomansimbi 4.8 6.3 6.1 4,957 19.3 25,662
Butambala 6.5 6.4 6.4 4,100 23.1 17,741
Buvuma 6.1 6.2 6.2 3,016 17.1 17,620
Gomba 5.1 6.7 6.6 7,279 25.7 28,326
Kalungu 5.3 6.4 6.1 6,552 21.4 30,598
Kampala 3.3 - 3.3 99,523 46.7 213,222
Kalangala 4.1 4.9 4.8 3,215 36.9 8,723
Kayunga 4.4 6.5 6.3 15,488 23.6 65,556
Kiboga 5.2 6.3 6 6,239 24.4 25,616
Kyankwanzi 5.5 6.7 6.5 8,954 22.1 40,589
Kyotera 4.3 6 5.7 7,143 18.9 37,722
Luwero 4.5 6 5.6 22,171 28.5 77,774
Lwengo 5.4 6.6 6.3 7,357 14.8 49,718
Lyantonde 4 6.5 5.9 3,572 21.2 16,854
Masaka 4.1 5.7 5 13,398 27.2 49,204
Mityana 4.7 6.1 5.6 13,215 23.8 55,552
Mpigi 5.2 5.5 5.4 14,742 34.5 42,705
Mubende 5 6.5 6.2 32,068 25.1 127,910
Mukono 3.8 5.2 4.7 36,213 37.4 96,944
Nakaseke 4.7 6.1 5.7 12,838 40.5 31,686
Nakasongola 4.9 6.7 6.4 9,455 29.5 32,010
Rakai 5.4 6.8 6.7 19,047 20.6 92,295
Ssembabule 5.1 6.4 6.3 6,704 14.6 45,828
Wakiso 4 4.9 4.1 135,400 40.5 333,929
Eastern Region
Amuria 6 8.1 7.9 25,084 47.8 52,431
Budaka 6.3 7.7 7.5 8,765 21.6 40,601
Bududa 5.4 6.5 6.4 9,489 26.9 35,306
Bugiri 5.9 7.7 7.3 22,881 30.2 75,846
Bukedea 6.4 8.1 8 5,403 13.9 38,945
Appendices i
Total Fertility Rate Has Birth Certificate District Urban Rural Uganda Number of Percent of Total Number registered under 5 who of children children are registered below 5 years Eastern Region
Bukwo 5.2 7.4 7 2,487 14.3 17,380
Bulambuli 5.6 5.8 5.8 6,097 21.6 28,270
Busia 4.7 6.4 6 14,673 24.9 58,812
Butaleja 7.2 8.2 8 7,848 15.6 50,448
Butebo 7.9 7.6 7.6 7,249 25.2 28,776
Buyende 8.4 8.2 8.3 16,468 23.3 70,732
Iganga 4.6 6.9 6.3 20,876 23.3 89,547
Jinja 4.5 6.1 5.4 28,785 37.8 76,202
Kaberamaido 6 7.9 7.8 7,862 20 39,349
Kaliro 5.3 7.9 7.7 12,215 26.5 46,088
Kamuli 5.3 7.3 7 34,486 38.6 89,370
Kapchorwa 4.7 5.6 5.2 3,336 20.2 16,475
Katakwi 4.4 6.8 6.6 15,390 55.1 27,954
Kibuku 6.4 7.8 7.7 12,774 31 41,253
Kumi 5.3 7.2 6.8 15,561 36.9 42,171
Kween 5.8 6.8 6.8 2,719 16.6 16,367
Luuka 5.5 7.2 7.1 8,035 18.3 43,944
Manafwa 6.2 7.2 7 10,270 15.8 64,990
Mayuge 5.2 7 6.8 31,381 34.2 91,704
Mbale 4.2 5.9 5.3 21,879 27.4 79,879
Namayingo 6.3 6.9 6.9 11,928 28.1 42,452
Namisindwa 6.3 7.3 7.2 5,707 14.9 38,382
Namutumba 5.7 8 7.8 16,517 32.8 50,327
Ngora 6.5 7.2 7.1 4,613 18.4 25,106
Pallisa 6.4 7.7 7.5 24,462 32.5 75,192
Serere 5.3 8 7.9 24,654 45.9 53,708
Sironko 5.3 6.4 6.2 10,086 24.9 40,464
Soroti 3.9 7 6.3 24,888 48 51,815
Tororo 4.4 6.7 6.3 28,994 31.8 91,269
Northern Region
Abim 5.1 7.1 6.8 8,330 43.3 19,231
Adjumani 4.1 6.7 6.2 12,380 28.2 43,830
Agago 6.1 8 7.7 22,409 51.3 43,648
Alebtong 6.2 7 7 9,953 25 39,848
Amolatar 6.2 7 6.9 10,884 43.6 24,973
Amudat 7.4 10.2 9.8 7,202 38.2 18,868
Amuru 8.8 7.2 7.3 13,763 39.3 34,995
Appendices ii
Total Fertility Rate Has Birth Certificate District Urban Rural Uganda Number of Percent of Total Number registered under 5 who of children children are registered below 5 years Northern Region
Apac 5.6 6.6 6.4 18,891 30.7 61,629
Arua 4.4 5.7 5.6 51,916 38.8 133,976
Dokolo 5.4 6.7 6.5 10,861 35.2 30,867
Gulu 3.9 6.7 4.9 18,537 43 43,067
Kaabong 5.2 7.9 7.6 7,497 26.5 28,243
Kitgum 4.9 7.6 6.5 17,779 49.9 35,610
Koboko 5.9 7.1 6.8 12,198 31.8 38,374
Kole 4.7 6.5 6.4 15,575 37.2 41,865
Kotido 7.1 8.1 7.7 9,537 30.4 31,416
Lamwo 7.6 7.6 7.6 12,460 50.7 24,591
Lira 4 6.2 5.4 27,235 41.7 65,297
Maracha 5.7 6.3 6.3 8,300 24.3 34,153
Moroto 4.6 7.5 7.0 5,333 28.5 18,728
Moyo 3.2 5.8 5.6 11,500 52.3 22,001
Nakapiripirit 5.9 7.7 7.7 8,684 31.4 27,699
Napak 5.8 7.5 6.7 8,679 32.4 26,816
Nebbi 4.8 6.5 6.2 16,521 23 71,741
Nwoya 7 7.5 7.4 8,037 31.3 25,665
Omoro 7.5 6.5 6.7 9,991 35.8 27,872
Otuke 5.2 7.3 7.2 9,639 50.5 19,102
Oyam 5.3 6.3 6.3 30,163 44.1 68,339
Pader 5.4 7.1 7.0 13,678 43.6 31,336
Pakwach 6.0 6.6 6.5 5,873 20.1 29,244
Yumbe 6.2 7.2 7.2 47,254 58 81,450
Zombo 5.8 6.9 6.7 5,568 12.5 44,631
Western Region
Buhweju 4.3 5.8 5.8 3,751 17.2 21,787
Buliisa 6.5 6.9 6.8 1,591 7.4 21,420
Bundibugyo 5.2 7.1 6.7 18,105 41.7 43,402
Bunyangabu 5.2 5.9 5.7 6682 21.8 30,631
Bushenyi 3.5 4.5 4.2 9,446 27.6 34,175
Hoima 4.0 6.3 5.8 20,592 19.2 107,362
Ibanda 4.4 5.5 4.9 6,293 15.8 39,715
Isingiro 5.1 5.8 5.7 27,165 30.9 88,026
Kabale 3.2 4.7 4.2 14,144 28.2 50,208 Kabarole 4.1 5.3 4.8 24,504 30.8 79,493
Kagadi 5.4 6.9 6.7 9,162 12.7 71,895
Appendices iii
Total Fertility Rate Has Birth Certificate District Urban Rural Uganda Number of Percent of Total Number registered under 5 who of children children are registered below 5 years Western Region
Kakumiro 5.5 7.0 6.9 7,471 12.2 61,114
Kamwenge 4.7 6.3 6.2 14,424 18 79,924
Kanungu 4.0 4.9 4.7 7,782 18.9 41,074
Kasese 4.7 6.6 6.1 51,370 39.5 130,140
Kibaale 4.0 7.2 7.0 3,075 10.2 30,157
Kiruhura 4.8 5.5 5.4 7,054 12.7 55,358
Kiryandongo 5.4 7.1 6.7 12,654 24.9 50,732
Kisoro 4.3 5.8 5.6 14,826 28.6 51,843
Kyegegwa 6.2 7.1 7.0 7,311 12.7 57,458
Kyenjojo 5.5 6.6 6.4 15,696 18.8 83,435
Masindi 4.7 6.2 5.7 11,299 22.3 50,748
Mbarara 3.6 4.9 4.2 20,343 27.8 73,138
Mitooma 4.1 5.3 5.2 5,100 16.2 31,519
Ntoroko 5.9 6.9 6.4 4,293 34.7 12,379
Ntungamo 4.7 5.8 5.6 13,491 16.1 83,685
Rubanda 4.0 4.9 4.8 3,555 10.5 34,004
Rubirizi 4.7 6.5 6.2 4,102 18.5 22,194
Rukiga 3.5 4.6 4.5 2944 19.1 15452
Rukungiri 3.5 5.0 4.7 15,522 31.1 49,943
Sheema 4.0 4.4 4.2 4,889 16.3 30,085
Total 4.1 6.5 5.8 1,830,491 30 6,107,155
Appendices iv
Table A.2: Adolescent Fertility Rate and Early Marriages by district
Adolescent motherhood Child Marriage among women aged 10-17 years
District Ever Given Percent Total Currently Widowed Divorced/ Sexually Birth married separated exposed Central Region Buikwe 6,230 14.9 41,692 3,173 137 316 3,626
Bukomansimbi 1,997 13.3 14,978 868 53 124 1,045
Butambala 1,296 12.3 10,502 704 18 87 809
Buvuma 1,476 25.5 5,796 702 14 79 795
Gomba 1,772 12 14,816 697 14 70 781 Kalangala 618 25 2,473
Kalungu 2,155 12.1 17,870 833 44 76 953 Kampala 20,166 13.4 149,937
Kayunga 5,736 15.3 37,493 2,897 99 319 3,315
Kiboga 1,883 13.9 13,581 750 38 69 857
Kyankwanzi 3,206 16.7 19,158 1,431 36 140 1,607
Kyotera 3,174 15 21,151 1,382 73 92 1,547
Luwero 6,517 14.2 45,785 2,989 128 283 3,400
Lwengo 3,488 13.2 26,466 1,826 57 104 1,987
Lyantonde 1,026 11.8 8,667 541 21 62 624
Masaka 3,218 11.8 27,250 1,301 32 117 1,450
Mityana 4,897 15.6 31,325 2,539 143 240 2,922
Mpigi 3,639 15.6 23,350 1,440 41 175 1,656
Mubende 11,007 17.5 63,068 5,470 193 498 6,161
Mukono 10,593 18.3 57,776 5,741 177 581 6,499
Nakaseke 3,129 17.8 17,536 1,507 73 180 1,760
Nakasongola 2,501 14.1 17,717 949 23 115 1,087
Rakai 4,275 15.9 26,969 2,425 96 124 2,645
Ssembabule 3,195 13.7 23,345 1,326 35 119 1,480
Wakiso 29,028 14.7 197,335 10,529 370 966 11,865 Eastern Region
Amuria 3,947 14.1 28,015 2,026 54 89 2,169
Budaka 3,078 14.3 21,597 1,433 33 81 1,547
Bududa 2,981 12.7 23,408 1,543 29 108 1,680
Bugiri 6,789 17.5 38,762 3,397 98 197 3,692
Bukedea 2,289 11.5 19,975 1,118 33 72 1,223
Bukwo 1,309 15.1 8,662 576 14 35 625
Bulambuli 2,754 15.1 18,226 1,628 47 120 1,795
Busia 5,340 15.7 34,014 2,106 50 138 2,294
Butaleja 3,867 16 24,135 2,198 59 108 2,365
Butebo 2,519 16.5 15,250 1,491 35 99 1,625
Iganga 8,634 15.8 54,561 4,623 158 437 5,218
Jinja 6,334 12.5 50,737 3,096 74 251 3,421
Appendices v
Adolescent motherhood Child Marriage among women aged 10-17 years District Ever Given Percent Total Currently Widowed Divorced/ Sexually Birth married separated exposed Kaberamaido 3,204 14.2 22,502 1,545 60 95 1,700
Kaliro 3,698 15.5 23,928 1,828 56 83 1,967
Kamuli 8,042 15.8 50,945 3,881 93 256 4,230
Kapchorwa 1,476 13.3 11,107 737 19 62 818
Katakwi 2,411 14.6 16,543 1,094 52 40 1,186
Kibuku 3,668 17.6 20,827 1,887 34 100 2,021
Kumi 2,821 11.5 24,453 1,175 27 55 1,257
Kween 1,133 12.3 9,212 580 15 50 645
Luuka 4,691 18.1 25,850 2,292 107 192 2,591
Mayuge 10,557 22.3 47,282 5,662 186 424 6,272
Mbale 9,622 18.2 52,731 4,346 126 305 4,777
Namayingo 4,675 22.9 20,382 2,205 60 170 2,435
Namisindwa 2,838 13.9 20,367 1,773 24 108 1,905
Namutumba 3,836 15.3 25,004 1,951 94 142 2,187
Ngora 1,801 12.2 14,772 641 10 16 667
Pallisa 4,718 18.5 25,484 2,551 114 127 2,792
Serere 4,240 14.7 28,859 2,265 25 180 2,470
Sironko 3,367 13.4 25,197 1,916 35 140 2,091
Soroti 5,111 16.6 30,867 2,393 101 162 2,656
Tororo 8,942 16.5 54,050 5,243 141 272 5,656 Northern Region
Abim 1,300 11.1 11,715 572 39 16 627
Adjumani 2,970 13 22,878 1,254 36 125 1,415
Agago 3,241 14.3 22,651 1,934 96 130 2,160
Alebtong 3,205 13.2 24,321 1,883 77 82 2,042
Amolatar 2,345 15.6 14,994 1,405 73 97 1,575
Amudat 1,450 15.4 9,398 1,075 12 23 1,110 Amuru 4,081 21.7 18,772 2,497 60 204 2,761
Apac 5,267 13.4 39,182 2,909 130 134 3,173
Arua 14,330 17.3 83,055 6,732 242 799 7,773
Dokolo 2,737 13.8 19,831 1,050 39 70 1,159
Kaabong 1,590 9 17,572 869 32 20 921
Kitgum 3,474 16.6 20,987 1,861 66 155 2,082
Koboko 2,977 14.2 21,023 1,173 26 100 1,299
Kole 4,267 16.6 25,682 2,963 120 148 3,231
Kotido 1,956 10.8 18,162 1,155 27 8 1,190
Lamwo 1,792 13.6 13,143 952 70 105 1,127
Lira 6,596 14.8 44,644 3,341 83 292 3,716
Maracha 2,637 14.2 18,618 1,189 23 142 1,354
Appendices vi
Adolescent motherhood Child Marriage among women aged 10-17 years District Ever Given Percent Total Currently Widowed Divorced/ Sexually Birth married separated exposed Moroto 1,488 16.1 9,249 1,200 24 10 1,234
Moyo 1,426 10 14,239 557 23 58 638
Nakapiripirit 1,806 11.7 15,487 1,396 76 17 1,489
Napak 2,575 19.1 13,508 1,207 57 18 1,282
Nebbi 4,327 17.3 24,990 1,913 49 261 2,223
Nwoya 2,324 17.8 13,042 1,438 16 148 1,602
Omoro 2,996 18 16,668 2,048 58 157 2,263
Otuke 1,521 14.2 10,677 791 21 43 855
Oyam 7,745 19 40,666 5,855 99 227 6,181
Pader 3,783 20.6 18,350 2,038 50 150 2,238
Pakwach 2,968 19.1 15,507 1,415 61 159 1,635
Yumbe 7,531 13.4 56,211 2,989 90 290 3,369
Zombo 4,458 19.3 23,139 2,569 42 212 2,823
Western Region
Buhweju 1,804 15.6 11,564 1,062 17 57 1,136
Buliisa 2,421 23.2 10,449 1,046 40 140 1,226
Bundibugyo 5,781 25.1 23,014 3,395 76 487 3,958 Bunyangabu 2,869 17.6 16,328 1,237 58 176 1,471
Bushenyi 2,587 10.6 24,499 1,201 46 85 1,332
Hoima 11,252 21.5 52,273 5,690 221 550 6,461 Ibanda 3,224 13 24,717 1,682 105 135 1,922
Isingiro 7,497 16.4 45,665 4,071 188 283 4,542
Kabale 2,030 9.1 22,294 1,133 77 53 1,263
Kagadi 5,597 16.5 33,864 2,525 97 312 2,934
Kakumiro 4,294 16.5 26,012 2,137 55 229 2,421
Kamwenge 5,550 14.9 37,317 2,512 114 252 2,878
Kanungu 2,989 11.8 25,353 1,820 78 108 2,006
Kasese 12,395 17.9 69,183 5,200 240 786 6,226
Kibaale 2,298 18 12,736 1,143 44 122 1,309
Kiruhura 5,366 17.8 30,165 2,039 129 141 2,309
Kiryandongo 5,172 19.6 26,414 3,414 121 201 3,736
Kisoro 2,811 9.3 30,272 1,695 99 95 1,889 Kyankwanzi 3,206 16.7 19,158 1,431 36 140 1,607
Kyegegwa 4,566 17.9 25,575 2,320 153 205 2,678
Kyenjojo 7,031 17.9 39,254 3,045 140 301 3,486
Masindi 5,104 19.1 26,770 2,679 63 312 3,054
Mbarara 5,086 11.3 45,121 2,489 158 215 2,862
Mitooma 2,420 12.6 19,169 1,234 52 78 1,364
Ntoroko 1,246 19 6,565 464 11 68 543
Appendices vii
Adolescent motherhood Child Marriage among women aged 10-17 years District Ever Given Percent Total Currently Widowed Divorced/ Sexually Birth married separated exposed Ntungamo 5,006 10.6 47,439 3,063 97 189 3,349
Rubanda 2,047 10.1 20,201 1,352 37 79 1,468
Rubirizi 1,319 10.3 12,827 514 27 62 603
Rukiga 847 8.6 9,808 416 11 29 456
Rukungiri 3,523 11 32,111 1,680 89 114 1,883
Sheema 2,053 9.8 20,857 898 26 77 1,001
Appendices viii
Table A.3: Distribution of households by Overcrowding Status and selected Background characteristics
Type of Dwelling
Overcrowded Permanent Temporary
Central Region Buikwe 53.6 40.9 5.1 Bukomansimbi 45.8 59.3 2.5 Butambala 51.2 49.9 1.4 Buvuma 50.5 67.4 29.1 Gomba 50.9 61.6 11.2 Kalangala 32.1 68.9 20.0 Kalungu 45.4 52.9 3.4 Kampala 46.3 12.0 0.1 Kayunga 60.6 46.4 15.4 Kiboga 51.1 52.7 12.3 Kyankwanzi 55.3 52.2 26.7 Kyotera 41.9 51.8 4.6 Luwero 51.8 37.7 5.4 Lwengo 48.0 58.1 2.6 Lyantonde 53.8 47.6 15.1 Masaka 41.3 36.5 2.4 Mityana 46.8 53.3 2.6 Mpigi 44.6 45.1 2.1 Mubende 52.0 67.1 9.3 Mukono 48.4 32.2 4.7 Nakaseke 49.4 47.2 11.8 Nakasongola 58.4 41.2 26.5 Rakai 50.4 67.4 10.3 Ssembabule 52.2 57.7 12.6 Wakiso 46.6 15.4 0.5
Eastern Region Amuria 67.4 8.8 83.5 Budaka 69.1 60.3 18.9 Bududa 63.6 87.3 6.9 Bugiri 69.9 36.7 35.1 Bukedea 68.8 27.8 57.4 Bukwo 72.0 52.6 45.3 Bulambuli 58.7 84.8 11.2 Busia 68.0 27.6 41.8 Butaleja 70.8 55.3 27.1 Butebo 72.4 55.6 28.8 Buyende 71.0 48.6 36.4 Iganga 60.9 51.3 6.2 Jinja 54.9 46.7 1.2 Kaberamaido 65.3 13.3 76.6 Kaliro 69.5 49.8 27.8 Kamuli 62.0 61.9 8.1
Appendices ix
Type of Dwelling
Overcrowded Permanent Temporary
Eastern Region Kapchorwa 58.0 77.0 16.8 Katakwi 62.2 8.7 84.2 Kibuku 73.9 52.1 28.4 Kumi 68.4 16.4 63.2 Kween 68.7 56.6 41.7 Luuka 63.7 67.5 7.1 Manafwa 58.5 77.3 12.6 Mayuge 65.4 58.7 18.8 Mbale 52.9 67.1 2.8 Namayingo 71.6 37.4 50.5 Namisindwa 59.0 81.0 11.1 Namutumba 68.0 55.1 20.8 Ngora 67.5 12.8 69.1 Pallisa 71.8 41.1 39.2 Serere 68.5 11.7 75.4 Sironko 49.8 85.7 3.5 Soroti 61.3 16.4 57.2 Tororo 64.9 47.1 32.1
Northern Region Abim 78.7 14.9 78.3 Adjumani 72.1 27.6 66.5 Agago 70.8 14.6 80.8 Alebtong 62.2 20.4 74.9 Amolatar 61.8 28.4 65.1 Amudat 88.4 22.8 75.1 Amuru 65.1 16.9 80.4 Apac 60.7 19.6 70.4 Arua 63.6 36 49.9 Dokolo 62.1 25.1 65.3 Gulu 58.0 15.8 58.2 Kaabong 82.0 15 81.2 Kitgum 66.1 17.6 67.7 Koboko 74.8 23.1 66.1 Kole 60.2 23.6 67.8 Kotido 83.3 15.3 80.7 Lamwo 64.6 13.7 82.9 Lira 54.0 31.4 42.8 Maracha 64.9 33.9 60.9 Moroto 76.8 25.2 66.8 Moyo 65.1 43.1 48.4 Nakapiripirit 83.5 12.9 85.3 Napak 76.0 21.6 76.3 Nebbi 67.7 14.8 74.7 Nwoya 66.1 10.2 86.5 Omoro 63.0 10.3 84.5
Appendices x
Type of Dwelling
Overcrowded Permanent Temporary
Northern Region Otuke 62.9 10.7 85.2 Oyam 61.1 17.3 73.8 Pader 66.9 10.4 83.3 Pakwach 70.1 15.4 80 Yumbe 83.6 28.7 68.1 Zombo 62.7 17 73.1
Western Region Buhweju 53.7 79 11.3 Buliisa 60.0 32.9 60.4 Bundibugyo 55.2 87.2 3.5 Bunyangabu 47.9 86.5 3.2 Bushenyi 41.9 68.7 1.6 Hoima 49.9 48.4 31.3 Ibanda 46.9 71.5 4.5 Isingiro 53.5 75.3 12.1 Kabale 38.6 80.9 0.9 Kabarole 38.8 72.3 2.6 Kagadi 54.3 71.4 14.8 Kakumiro 56.5 66.9 19.1 Kamwenge 52.6 73.4 17.1 Kanungu 42.9 79.1 6.5 Kasese 55.9 70.2 5.8 Kibaale 54.4 76.3 13.4 Kiruhura 55.6 63.6 15.6 Kiryandongo 66.3 20.2 60.9 Kisoro 47.0 85.7 0.9 Kyegegwa 56.1 69.1 22.8 Kyenjojo 49.7 74.6 13.3 Masindi 53.2 32.2 34 Mbarara 43.8 57.5 2.1 Mitooma 47.2 79.5 5.7 Ntoroko 49.2 72 21.4 Ntungamo 52.5 81.8 5 Rubanda 44.9 93.4 1.9 Rubirizi 49.1 80.6 4.7 Rukiga 37.8 91.4 2 Rukungiri 42.3 84.2 3.8 Sheema 41.5 75.8 1.9
Appendices xi
Table A.4: Source of Drinking water by District
Piped Protected Unprotecte River/ Vendor/ Gravity Improved Number of water into Rain Bottled District Borehole well/ d well/ Stream/ Tanker flow Other water Household dwelling water water spring spring Lake truck scheme source s /yard
Central Region
Buikwe 24,765 12,948 44,974 6,603 4,238 3,006 312 473 176 338 93,766 97,833
Bukomansimbi 1,856 7,195 6,197 12,984 1,651 751 184 604 34 2,872 16,510 34,328
Butambala 1,973 6,039 8,552 4,194 226 406 90 111 76 11 18,009 21,678
Buvuma 259 5,536 1,468 1,127 14,849 857 428 36 397 162 7,923 25,119
Gomba 1,181 12,040 4,410 13,003 2,578 735 21 427 172 673 18,618 35,240
Kalangala 3,810 3,238 972 1,290 8,730 549 1,141 98 189 24 12,148 20,041
Kalungu 5,672 13,638 6,393 10,704 2,205 2,169 145 385 34 60 27,894 41,405
Kampala 341,841 3,864 38,627 5,527 1,092 14,477 478 1,924 5,081 1,495 543,904 414,406
Kayunga 4,751 51,463 5,267 7,792 4,397 1,435 64 418 113 262 64,592 75,962
Kiboga 4,348 10,063 4,555 10,022 2,479 1,431 121 787 68 136 23,167 34,010
Kyankwanzi 2,227 21,420 1,699 13,089 7,039 762 198 448 107 698 27,086 47,687
Kyotera 7,511 7,526 6,083 25,946 2,825 2,261 171 631 185 112 25,418 53,251
Luwero 16,242 66,473 3,513 14,326 1,512 1,613 49 986 136 359 95,730 105,209
Lwengo 2,657 14,621 5,770 29,922 908 5,703 124 1,778 134 136 26,387 61,753
Lyantonde 2,177 1,716 863 13,319 355 688 5 1,222 239 39 7,373 20,623
Masaka 31,281 12,336 8,362 15,586 5,553 1,228 104 652 139 253 65,283 75,494
Mityana 10,613 17,770 11,220 32,719 3,301 1,822 235 1,464 142 379 46,256 79,665
Mpigi 5,903 16,318 16,082 14,908 2,998 2,655 279 918 64 263 42,067 60,388
Mubende 16,318 25,587 9,103 84,141 9,613 1,804 615 2,482 287 1,150 60,407 151,100
Mukono 32,554 41,625 34,150 15,671 9,109 5,576 1,212 3,143 269 851 127,012 144,160
Nakaseke 3,651 25,678 1,624 8,020 2,575 409 135 586 108 262 33,613 43,048
Nakasongola 4,961 17,135 930 6,502 4,568 377 95 661 215 1,166 27,215 36,610
Rakai 3,561 5,340 3,048 35,184 10,615 1,725 106 3,162 180 218 17,264 63,139
Ssembabule 1,028 7,101 2,226 38,000 2,270 2,283 59 1,956 99 308 13,152 55,330
Wakiso 256,586 58,392 91,535 35,616 8,478 30,420 954 16,501 1,958 1,023 532,249 501,463
Eastern Region
Amuria 581 41,533 1,985 3,451 328 65 60 19 5 207 44,336 48,234
Budaka 874 22,135 10,179 3,112 315 415 39 10 5 104 33,680 37,188
Bududa 2,731 754 20,615 6,523 4,248 63 1,647 250 8 9 28,176 36,848
Bugiri 3,956 42,683 10,914 13,768 1,821 998 82 55 57 135 59,633 74,469
Bukedea 1,198 19,589 11,734 2,900 624 92 72 92 19 95 33,095 36,415
Bukwo 3,792 404 2,682 974 5,994 30 2,683 20 17 21 13,029 16,617
Bulambuli 2,587 9,613 9,740 3,801 6,632 516 899 76 16 98 25,086 33,978
Busia 8,444 32,573 16,032 4,571 2,395 320 127 55 102 150 62,092 64,769
Butaleja 755 38,924 1,131 2,937 269 111 4 16 14 201 41,219 44,362
Appendices xii
Piped Protected Unprotecte River/ Vendor/ Gravity Improved Number of water into Rain Bottled District Borehole well/ d well/ Stream/ Tanker flow Other water Household dwelling water water spring spring Lake truck scheme source s /yard
Eastern Region
Butebo 545 12,256 9,904 1,971 130 27 40 19 - 25 22,871 24,917
Buyende 1,096 51,492 436 3,484 3,829 396 9 63 31 363 53,844 61,199
Iganga 13,198 72,810 6,164 8,192 501 961 205 67 68 306 99,235 102,472
Jinja 55,273 30,326 14,398 1,592 685 2,433 239 133 181 98 131,605 105,358
Kaberamaido 458 32,542 2,105 2,812 534 78 116 23 11 81 35,449 38,760
Kaliro 911 38,930 268 1,214 1,107 262 25 19 34 154 40,485 42,924
Kamuli 3,453 80,189 2,700 4,841 1,570 524 22 126 79 186 88,144 93,690
Kapchorwa 3,495 163 11,244 3,012 2,007 52 1,463 19 26 15 18,090 21,496
Katakwi 1,134 27,259 852 1,196 166 27 21 47 7 35 29,932 30,744
Kibuku 635 30,506 2,358 1,401 332 143 4 18 13 36 33,693 35,446
Kumi 2,080 22,487 10,805 3,765 881 380 53 39 29 229 36,270 40,748
Kween 2,004 2,780 7,184 3,030 2,374 33 363 48 11 32 13,977 17,859
Luuka 1,658 36,498 3,485 2,009 262 257 76 28 10 76 42,798 44,359
Manafwa 755 12,807 14,360 2,277 496 56 127 33 13 55 28,528 30,979
Mayuge 6,988 42,058 17,720 18,133 8,359 1,070 248 63 101 600 71,770 95,340
Mbale 35,862 25,289 32,304 7,380 3,163 1,107 2,884 106 98 365 115,958 108,558
Namayingo 1,057 16,046 1,467 4,891 18,591 261 95 315 83 290 19,834 43,096
Namisindwa 4,505 2,585 24,905 4,907 3,197 72 1,432 175 16 42 36,924 41,836
Namutumba 1,783 32,637 3,407 6,478 770 139 24 36 5 92 38,910 45,371
Ngora 234 20,452 1,078 1,447 235 123 30 26 13 45 21,990 23,683
Pallisa 771 30,560 5,498 2,596 539 601 47 21 25 76 36,992 40,734
Serere 362 43,550 1,316 1,506 721 76 30 40 10 125 45,460 47,736
Sironko 12,499 7,685 21,520 4,951 5,826 254 2,891 179 17 40 54,037 55,862
Soroti 9,346 37,009 4,654 2,686 516 328 37 25 119 201 54,622 54,921
Tororo 13,353 54,212 14,725 18,103 875 654 185 55 117 213 87,432 102,492
Northern Region
Abim 567 16,884 291 213 39 18 17 36 3 14 18,184 18,082
Adjumani 3,312 34,961 387 631 1,530 393 25 4 3 69 40,153 41,315
Agago 467 30,449 1,514 6,969 3,243 41 217 357 34 85 33,133 43,376
Alebtong 1,349 13,812 15,420 14,802 630 53 46 56 3 57 30,853 46,228
Amolatar 346 26,744 22 26 564 202 - 25 26 39 27,376 27,994
Amudat 247 8,532 66 1,774 4,529 50 22 249 2 33 9,287 15,504
Amuru 2,110 12,191 4,116 14,523 3,048 261 90 27 150 134 18,877 36,650
Apac 1,592 60,915 1,742 3,805 2,828 119 38 268 95 218 65,262 71,620
Arua 14,310 50,981 40,767 15,772 22,385 328 819 735 157 373 113,228 146,627
Dokolo 1,245 22,185 6,093 4,575 624 36 153 18 5 23 30,427 34,957
Gulu 11,791 24,743 8,591 8,274 1,440 240 62 71 184 45 50,331 55,441
Appendices xiii
Piped Protected Unprotecte River/ Vendor/ Gravity Improved Number of water into Rain Bottled District Borehole well/ d well/ Stream/ Tanker flow Other water Household dwelling water water spring spring Lake truck scheme source s /yard
Northern Region
Kaabong 2,222 20,372 135 1,491 4,390 37 57 283 7 188 24,225 29,182
Kitgum 2,621 29,966 342 2,801 3,451 48 94 270 28 76 34,399 39,697
Koboko 3,466 10,179 6,286 7,181 2,502 60 443 40 40 74 22,501 30,271
Kole 2,518 19,219 11,474 14,343 145 300 201 94 142 89 33,780 48,525
Kotido 2,604 19,389 255 1,631 1,539 100 41 349 36 237 24,759 26,181
Lamwo 739 19,860 266 1,345 4,952 21 59 70 80 76 21,586 27,468
Lira 22,527 29,494 23,286 11,976 547 697 149 69 74 196 87,243 89,015
Maracha 2,301 10,484 15,822 6,440 757 43 258 26 63 78 29,104 36,272
Moroto 1,061 17,409 83 490 2,589 11 22 240 59 102 19,300 22,066
Moyo 5,039 16,744 818 357 1,343 58 1,381 35 7 85 27,474 25,867
Nakapiripirit 932 18,997 162 1,312 3,416 15 421 50 23 73 21,332 25,401
Napak 569 21,959 234 1,794 1,219 26 501 584 1 161 24,187 27,048
Nebbi 1,495 27,249 5,243 2,501 10,909 55 15 21 64 19 34,431 47,571
Nwoya 819 5,926 3,396 13,271 2,624 27 96 31 4 17 10,411 26,211
Omoro 1,867 12,905 4,421 10,790 1,472 58 14 15 6 24 19,460 31,572
Otuke 588 12,802 1,700 6,313 394 15 72 35 7 19 15,505 21,945
Oyam 3,346 33,897 12,989 24,156 911 187 474 115 50 411 51,588 76,536
Pader 1,337 21,884 1,845 5,636 3,094 45 134 103 47 58 26,009 34,183
Pakwach 4,766 10,290 305 1,742 12,538 116 32 23 12 40 18,696 29,864
Yumbe 1,405 39,436 1,677 9,186 11,172 64 267 139 4 423 43,509 63,773
Zombo 1,378 5,021 28,271 8,524 8,181 142 790 38 19 356 36,049 52,720
Western Region
Buhweju 1,765 1,239 8,381 6,797 5,414 139 867 173 58 79 13,858 24,912
Buliisa 3,667 9,001 1,532 1,722 4,243 343 828 20 60 186 18,414 21,602
Bundibugyo 17,460 1,000 3,834 3,036 17,114 157 1,935 61 45 136 37,780 44,778
Bunyangabu 8,229 7,345 5,008 4,388 9,452 290 1,165 113 18 60 27,795 36,068
Bushenyi 8,264 3,507 17,663 18,191 2,204 572 447 372 64 86 34,448 51,370
Hoima 10,570 34,103 36,736 22,853 16,072 2,323 1,036 574 455 677 88,149 125,399
Ibanda 15,958 5,615 5,906 19,694 5,981 547 813 226 62 145 37,890 54,947
Isingiro 14,972 9,625 5,308 38,839 17,164 3,354 3,416 8,352 142 451 53,345 101,623
Kabale 14,068 1,278 22,574 2,880 3,222 555 6,756 234 89 101 52,960 51,757
Kabarole 16,275 17,969 10,528 10,054 10,644 436 4,143 527 232 328 56,094 71,136
Kagadi 2,728 22,620 19,803 18,224 9,358 782 239 218 48 124 47,700 74,144
Kakumiro 887 32,898 5,482 15,176 7,486 761 290 174 61 256 40,400 63,471
Kamwenge 5,675 21,441 15,746 29,850 10,380 826 3,862 386 137 664 51,174 88,967
Kanungu 9,827 2,946 17,007 11,023 12,163 402 2,265 202 21 200 40,037 56,056
Kasese 69,294 8,726 16,021 7,573 27,296 2,455 7,359 262 110 310 147,046 139,406
Appendices xiv
Piped Protected Unprotecte River/ Vendor/ Gravity Improved Number of water into Rain Bottled District Borehole well/ d well/ Stream/ Tanker flow Other water Household dwelling water water spring spring Lake truck scheme source s /yard
Western Region
Kibaale 906 7,525 7,233 11,161 3,223 110 75 110 43 222 15,946 30,608
Kiruhura 1,319 5,024 4,425 48,241 2,710 2,303 38 2,296 543 253 14,095 67,152
Kiryandongo 2,835 35,146 4,141 6,238 2,392 464 221 170 91 472 43,568 52,170
Kisoro 20,988 993 10,989 13,755 6,197 713 2,625 5,759 50 179 57,863 62,248
Kyegegwa 1,155 9,267 3,872 40,752 3,887 529 146 216 102 116 15,520 60,042
Kyenjojo 5,576 16,290 18,063 39,730 8,729 778 1,038 249 172 819 44,234 91,444
Masindi 10,510 22,039 20,189 8,019 2,772 629 218 200 61 183 56,253 64,820
Mbarara 49,031 4,281 13,308 27,072 6,126 3,347 4,317 4,360 261 669 97,059 112,772
Mitooma 2,181 3,042 12,880 15,040 5,024 234 1,034 134 75 156 20,607 39,800
Ntoroko 1,755 3,774 804 3,518 2,315 35 1,499 38 132 47 9,441 13,917
Ntungamo 14,781 12,111 27,932 27,163 13,706 553 3,811 561 112 1,029 70,924 101,759
Rubanda 3,973 1,261 22,819 5,387 4,474 408 3,815 1,074 12 100 36,035 43,323
Rubirizi 11,036 1,928 2,927 2,941 9,054 315 22 361 13 151 25,774 28,748
Rukiga 5,297 853 8,365 2,731 3,343 70 1,897 113 8 43 21,484 22,720
Rukungiri 10,652 3,654 24,779 14,715 11,669 1,104 2,268 316 241 137 49,829 69,535
Sheema 11,131 4,277 9,054 16,321 1,866 563 2,022 492 29 57 35,943 45,812
Total 1,439,800 2,453,055 1,198,820 1,309,834 559,141 128,029 91,081 76,988 16,944 30,378 5,996,563 7,304,070
Appendices xv
Table A.5: Distribution of Households by Distance to drinking Water source by district
District On premise Less than 1 Km Over 1 All households km Number Percent Number Percent Number Percent Number Percent
Central Region
Buikwe 31,785 33 41,700 43 25 24,348 100 24,348 Bukomansimbi 4,970 15 14,999 44 42 14,359 100 14,359 Butambala 3,877 18 12,049 56 27 5,752 100 5,752 Buvuma 10,421 42 9,838 39 19 4,860 100 4,860 Gomba 5,997 17 17,517 50 33 11,726 100 11,726 Kalangala 5,257 26 13,137 66 8 1,647 100 1,647 Kalungu 10,912 26 15,863 38 35 14,630 100 14,630 Kampala 309,454 75 92,118 22 3 12,834 100 12,834 Kayunga 18,428 24 36,819 49 27 20,715 100 20,715 Kiboga 8,224 24 16,306 48 28 9,480 100 9,480 Kyankwanzi 9,067 19 15,910 33 48 22,710 100 22,710 Kyotera 10,147 19 24,362 46 35 18,742 100 18,742 Luwero 36,322 35 51,648 49 16 17,239 100 17,239 Lwengo 16,631 27 24,157 39 34 20,965 100 20,965 Lyantonde 3,581 17 8,319 40 42 8,723 100 8,723 Masaka 29,581 39 31,642 42 19 14,271 100 14,271 Mityana 20,093 25 41,295 52 23 18,277 100 18,277 Mpigi 12,738 21 29,131 48 31 18,519 100 18,519 Mubende 31,986 21 61,510 41 38 57,604 100 57,604 Mukono 52,996 37 66,421 46 17 24,743 100 24,743 Nakaseke 11,414 27 22,777 53 21 8,857 100 8,857 Nakasongola 7,868 22 13,824 38 41 14,918 100 14,918 Rakai 8,005 13 24,017 38 49 31,117 100 31,117 Ssembabule 6,074 11 23,960 43 46 25,296 100 25,296 Wakiso 310,423 62 146,829 29 9 44,211 100 44,211
Eastern Region
Amuria 5,508 11 22,074 46 43 20,652 100 20,652 Budaka 5,672 15 23,016 62 23 8,500 100 8,500 Bududa 3,645 10 24,498 67 24 8,705 100 8,705 Bugiri 14,719 20 38,951 52 28 20,799 100 20,799 Bukedea 4,538 13 15,810 43 44 16,067 100 16,067 Bukwo 4,097 25 9,309 56 19 3,211 100 3,211 Bulambuli 5,801 17 20,922 62 21 7,255 100 7,255
Appendices xvi
Busia 14,297 22 33,810 52 26 16,662 100 16,662 Butaleja 6,003 14 25,141 57 30 13,218 100 13,218 Butebo 6,008 24 11,552 46 30 7,357 100 7,357 Buyende 8,266 14 17,925 29 57 35,008 100 35,008 Iganga 37,682 37 46,565 45 18 18,225 100 18,225 Jinja 51,691 49 42,516 40 11 11,151 100 11,151 Kaberamaido 3,991 10 16,974 44 46 17,795 100 17,795 Kaliro 9,096 21 21,844 51 28 11,984 100 11,984 Kamuli 21,136 23 41,228 44 33 31,326 100 31,326 Kapchorwa 4,109 19 12,868 60 21 4,519 100 4,519 Katakwi 4,336 14 14,026 46 40 12,382 100 12,382 Kibuku 5,959 17 18,840 53 30 10,647 100 10,647 Kumi 7,031 17 16,965 42 41 16,752 100 16,752 Kween 2,870 16 10,458 59 25 4,531 100 4,531 Luuka 11,515 26 24,121 54 20 8,723 100 8,723 Manafwa 3,573 12 18,128 59 30 9,278 100 9,278 Mayuge 18,676 20 47,352 50 31 29,312 100 29,312 Mbale 44,924 41 49,878 46 13 13,756 100 13,756 Namayingo 7,717 18 17,747 41 41 17,632 100 17,632 Namisindwa 5,965 14 24,098 58 28 11,773 100 11,773 Namutumba 7,430 16 21,248 47 37 16,693 100 16,693 Ngora 3,385 14 11,640 49 37 8,658 100 8,658 Pallisa 7,037 17 21,936 54 29 11,761 100 11,761 Serere 6,813 14 24,543 51 34 16,380 100 16,380 Sironko 22,599 41 27,103 49 11 6,160 100 6,160 Soroti 14,694 27 25,040 46 28 15,187 100 15,187 Tororo 23,060 23 41,477 41 37 37,955 100 37,955
Northern Region
Abim 3,553 20 8,543 47 33 5,986 100 5,986 Adjumani 11,883 29 22,140 54 18 7,292 100 7,292 Agago 11,435 26 20,421 47 27 11,520 100 11,520 Alebtong 5,495 12 20,465 44 44 20,268 100 20,268 Amolatar 4,390 16 11,453 41 43 12,151 100 12,151 Amudat 2,441 16 3,180 21 64 9,883 100 9,883 Amuru 9,588 26 18,948 52 22 8,114 100 8,114 Apac 12,135 17 27,367 38 45 32,118 100 32,118 Arua 30,658 21 75,947 52 27 40,022 100 40,022 Dokolo 3,751 11 17,963 51 38 13,243 100 13,243
Appendices xvii
Gulu 23,821 43 25,169 45 12 6,451 100 6,451 Kaabong 5,909 20 13,049 45 35 10,224 100 10,224 Kitgum 12,704 32 15,395 39 29 11,598 100 11,598 Koboko 9,636 32 15,690 52 16 4,945 100 4,945 Kole 10,901 23 22,315 46 32 15,309 100 15,309 Kotido 6,905 26 8,833 34 40 10,443 100 10,443 Lamwo 5,959 22 12,485 46 33 9,024 100 9,024 Lira 26,149 29 37,069 42 29 25,797 100 25,797 Maracha 9,444 26 21,288 59 15 5,540 100 5,540 Moroto 10,875 49 6,150 28 23 5,041 100 5,041 Moyo 4,379 17 16,697 65 19 4,791 100 4,791 Nakapiripirit 8,752 35 10,345 41 25 6,304 100 6,304 Napak 6,428 24 8,546 32 45 12,074 100 12,074 Nebbi 12,151 26 25,888 54 20 9,532 100 9,532 Nwoya 6,480 25 12,142 46 29 7,589 100 7,589 Omoro 7,645 24 16,601 53 23 7,326 100 7,326 Otuke 2,822 13 9,685 44 43 9,438 100 9,438 Oyam 16,004 21 35,947 47 32 24,585 100 24,585 Pader 10,026 29 14,745 43 28 9,412 100 9,412 Pakwach 5,698 19 11,497 39 42 12,669 100 12,669 Yumbe 11,065 17 23,493 37 46 29,215 100 29,215 Zombo 8,850 17 35,285 67 16 8,585 100 8,585
Western Region
Buhweju 1,591 6 13,377 54 40 9,944 100 9,944 Buliisa 5,007 23 10,788 50 27 5,807 100 5,807 Bundibugyo 11,771 26 18,544 41 32 14,463 100 14,463 Bunyangabu 7,894 22 18,839 52 26 9,335 100 9,335 Bushenyi 8,802 17 33,671 66 17 8,897 100 8,897 Hoima 31,533 25 58,078 46 29 35,788 100 35,788 Ibanda 13,120 24 27,824 51 26 14,003 100 14,003 Isingiro 18,713 18 31,328 31 51 51,582 100 51,582 Kabale 11,855 23 24,968 48 29 14,934 100 14,934 Kabarole 22,901 32 36,467 51 17 11,768 100 11,768 Kagadi 7,343 10 48,137 65 25 18,664 100 18,664 Kakumiro 8,333 13 36,110 57 30 19,028 100 19,028 Kamwenge 14,896 17 48,070 54 29 26,001 100 26,001 Kanungu 7,552 14 32,054 57 29 16,450 100 16,450 Kasese 43,553 31 61,625 44 25 34,228 100 34,228
Appendices xviii
Kibaale 4,787 16 19,066 62 22 6,755 100 6,755 Kiruhura 8,308 12 31,901 48 40 26,943 100 26,943 Kiryandongo 12,927 25 26,487 51 25 12,756 100 12,756 Kisoro 12,436 20 23,983 39 42 25,829 100 25,829 Kyegegwa 5,739 10 32,393 54 37 21,910 100 21,910 Kyenjojo 13,970 15 50,000 55 30 27,474 100 27,474 Masindi 16,225 25 35,882 55 20 12,713 100 12,713 Mbarara 48,899 43 38,453 34 23 25,420 100 25,420 Mitooma 4,010 10 23,558 59 31 12,232 100 12,232 Ntoroko 3,682 27 6,342 46 28 3,893 100 3,893 Ntungamo 13,563 13 53,820 53 34 34,376 100 34,376 Rubanda 3,644 8 18,092 42 50 21,587 100 21,587 Rubirizi 5,832 20 13,160 46 34 9,756 100 9,756 Rukiga 1,984 9 13,774 61 31 6,962 100 6,962 Rukungiri 13,526 20 41,843 60 20 14,166 100 14,166 Sheema 7,937 17 29,066 63 19 8,809 100 8,809 Uganda 2,090,359 29 3,278,192 45 27 1,935,519 100 1,935,519
Appendices xix
Table A.6: Type of Kitchen at Household
District Inside, Inside, no Outside, Make shift Open Total Total number of specific specific built space households room room Central Region
Kalangala 4.3 18.7 20.0 9.9 47.1 100 20,041
Kampala 18.1 13.5 19.3 5.1 44.0 100 414,406
Kiboga 3.3 3.9 46.2 13.1 33.5 100 34,010
Luwero 5.0 4.9 45.5 11.7 32.9 100 105,209
Masaka 5.9 7.5 43.4 8.0 35.2 100 75,494
Mpigi 3.5 5.5 47.2 12.6 31.3 100 60,388
Mubende 2.9 4.0 51.0 13.5 28.6 100 151,100
Mukono 7.8 6.2 44.5 10.1 31.5 100 144,160
Nakasongola 4.3 7.7 45.5 9.0 33.5 100 36,610
Rakai 2.9 4.2 55.8 11.8 25.2 100 116,390
Ssembabule 2.8 5.1 56.8 11.2 24.1 100 55,330
Kayunga 2.7 3.3 54.7 10.9 28.3 100 75,962
Wakiso 14.9 9.9 33.6 6.5 35.1 100 501,463
Lyantonde 4.0 5.3 50.0 10.4 30.4 100 20,623
Mityana 3.5 4.0 46.4 16.1 30.0 100 79,665
Nakaseke 3.3 6.4 50.2 11.0 29.1 100 43,048
Buikwe 6.0 5.5 42.5 11.3 34.6 100 97,833
Bukomansimbi 2.3 2.3 63.5 10.7 21.1 100 34,328
Butambala 2.9 3.6 57.6 9.8 26.2 100 21,678
Buvuma 3.4 13.2 17.9 10.2 55.3 100 25,119
Gomba 2.8 3.3 54.3 12.2 27.4 100 35,240
Kalungu 2.9 4.5 59.0 8.9 24.8 100 41,405
Kyankwanzi 3.3 3.3 43.0 15.7 34.8 100 47,687
Lwengo 4.0 6.5 59.5 10.1 19.9 100 61,753
Eastern Region
Bugiri 3.9 3.3 65.7 6.7 20.4 100 74,469
Busia 4.5 6.3 57.9 6.6 24.6 100 64,769
Iganga 4.0 3.5 50.9 8.4 33.3 100 102,472
Jinja 10.1 8.6 35.6 10.7 34.9 100 105,358
Kamuli 3.7 2.9 60.4 11.0 21.9 100 93,690
Kapchorwa 13.0 12.6 56.7 10.4 7.3 100 21,496
Katakwi 6.0 2.5 54.8 14.7 22.0 100 30,744
Kumi 7.6 3.5 69.5 5.5 14.0 100 40,748
Mbale 8.1 5.0 47.1 10.2 29.5 100 108,558
Pallisa 4.7 3.0 81.3 3.8 7.1 100 65,651
Soroti 17.1 7.8 48.9 4.7 21.5 100 54,921
Appendices xx
District Inside, Inside, no Outside, Make shift Open Total Total number of specific specific built space households room room Eastern Region
Tororo 5.9 3.4 68.1 6.7 16.0 100 102,492
Kaberamaido 13.9 7.7 60.2 4.7 13.5 100 38,760
Mayuge 4.8 5.2 57.3 7.9 24.9 100 95,340
Sironko 6.2 4.6 60.2 12.2 16.8 100 55,862
Amuria 10.8 4.3 58.7 8.5 17.7 100 48,234
Budaka 3.2 1.9 83.9 4.1 7.0 100 37,188
Bududa 10.2 3.7 61.2 14.8 10.1 100 36,848
Bukedea 7.4 3.2 69.5 6.2 13.7 100 36,415
Bukwo 15.7 15.9 55.7 7.0 5.7 100 16,617
Butaleja 3.4 2.0 70.9 9.2 14.4 100 44,362
Kaliro 3.7 2.6 75.0 5.5 13.1 100 42,924
Manafwa 6.4 3.8 65.7 9.7 14.3 100 72,815
Namutumba 3.6 2.7 68.0 7.2 18.5 100 45,371
Bulambuli 9.0 6.0 53.2 13.5 18.2 100 33,978
Buyende 4.1 2.7 65.4 10.2 17.7 100 61,199
Kibuku 3.3 2.4 83.6 3.5 7.2 100 35,446
Kween 20.1 15.2 51.3 7.3 6.0 100 17,859
Luuka 2.5 2.9 69.3 9.0 16.4 100 44,359
Namayingo 3.8 5.9 58.9 6.1 25.2 100 43,096
Ngora 4.6 5.4 75.4 4.2 10.4 100 23,683
Serere 10.8 3.8 65.3 8.3 11.8 100 47,736
Northern Region
Adjumani 17.6 9.7 31.5 7.1 34.2 100 41,315
Apac 15.9 5.2 63.0 4.4 11.6 100 71,620
Arua 11.8 7.4 55.8 4.2 20.9 100 146,627
Gulu 20.9 35.7 29.1 3.2 11.1 100 55,441
Kitgum 25.4 37.6 18.9 4.6 13.4 100 39,697
Kotido 5.3 8.4 10.2 6.4 69.6 100 26,181
Lira 12.0 8.0 51.5 3.2 25.2 100 89,015
Moroto 4.1 4.1 3.9 11.4 76.4 100 22,066
Moyo 10.6 7.6 45.1 7.4 29.3 100 25,867
Nebbi 8.4 6.6 54.8 3.4 26.7 100 77,435
Nakapiripirit 5.7 9.3 6.1 18.1 60.8 100 25,401
Pader 24.1 39.2 22.7 4.9 9.1 100 34,183
Yumbe 6.2 2.5 49.3 6.5 35.5 100 63,773
Abim 8.9 13.3 43.4 8.5 26.0 100 18,082
Amolatar 11.2 7.3 59.0 4.7 17.8 100 27,994
Amuru 17.1 37.7 32.8 5.7 6.6 100 36,650
Appendices xxi
District Inside, Inside, no Outside, Make shift Open Total Total number of specific specific built space households room room Northern Region
Dokolo 8.0 4.0 73.7 3.8 10.4 100 34,957
Kaabong 5.8 21.8 9.4 22.9 40.2 100 29,182
Koboko 8.2 3.3 59.8 5.0 23.7 100 30,271
Maracha 6.6 5.2 76.4 2.4 9.5 100 36,272
Oyam 13.4 7.7 63.4 7.3 8.2 100 76,536
Agago 24.8 35.3 24.5 3.4 12.0 100 43,376
Alebtong 11.2 4.9 63.4 4.5 15.9 100 46,228
Amudat 16.1 16.3 16.0 6.5 45.0 100 15,504
Kole 12.8 7.3 65.1 5.7 9.2 100 48,525
Lamwo 21.9 45.0 19.2 5.2 8.6 100 27,468
Napak 4.2 8.3 6.3 16.4 64.9 100 27,048
Nwoya 24.9 37.7 25.6 2.3 9.4 100 26,211
Otuke 9.7 6.6 52.7 5.2 25.7 100 21,945
Zombo 10.4 12.6 63.4 2.4 11.1 100 52,720
Omoro 24.1 38.3 26.9 5.1 5.6 100 31,572
Western Region
Bundibugyo 4.6 3.0 46.7 14.5 31.2 100 44,778
Bushenyi 5.4 5.3 73.6 6.5 9.3 100 51,370
Hoima 4.2 3.5 46.9 13.7 31.7 100 125,399
Kabale 4.1 3.2 65.7 13.1 14.0 100 74,477
Kabarole 3.4 1.5 64.6 14.6 15.9 100 107,204
Kasese 6.5 3.3 52.4 9.3 28.4 100 139,406
Kibaale 2.6 2.4 59.2 13.1 22.6 100 30,608
Kisoro 4.0 2.7 64.8 12.7 15.7 100 62,248
Masindi 6.2 5.2 47.9 8.5 32.1 100 64,820
Mbarara 5.6 6.6 55.4 8.5 23.9 100 112,772
Ntungamo 2.0 2.4 68.9 9.6 17.2 100 101,759
Rukungiri 1.9 1.9 73.7 9.3 13.1 100 69,535
Kamwenge 2.6 4.6 60.0 14.3 18.5 100 88,967
Kanungu 2.2 1.8 71.6 11.3 13.1 100 56,056
Kyenjojo 2.3 2.1 59.8 19.3 16.5 100 91,444
Buliisa 6.5 4.8 34.7 8.1 45.9 100 21,602
Ibanda 2.9 2.2 68.6 10.1 16.2 100 54,947
Isingiro 4.6 4.5 53.7 14.0 23.2 100 101,623
Kiruhura 2.0 2.6 62.8 8.4 24.2 100 67,152
Buhweju 3.3 3.3 71.5 10.2 11.7 100 24,912
Kiryandongo 10.9 6.6 42.3 6.9 33.3 100 52,170
Kyegegwa 3.1 3.7 57.1 12.4 23.8 100 60,042
Appendices xxii
District Inside, Inside, no Outside, Make shift Open Total Total number of specific specific built space households room room Western
Mitooma 2.3 2.0 75.7 11.7 8.3 100 39,800
Ntoroko 3.2 4.1 37.3 12.4 43.0 100 13,917
Rubirizi 2.1 3.0 63.5 12.6 18.7 100 28,748
Sheema 2.6 2.3 75.9 7.5 11.8 100 45,812
Kagadi 2.1 2.4 60.4 13.0 22.1 100 74,144
Kakumiro 2.3 3.2 51.4 12.8 30.3 100 63,471
Rubanda 2.3 1.5 74.8 12.8 8.6 100 43,323
Total 7.9 7.0 51.2 9.0 24.9 100 7,304,070
Appendices xxiii
Table A.7: Distribution of households by number of Meals taken in a day
District 1 Meal 2 Meals 3 or more meals Total households
Number Percent Number Percent Number Percent Number Percent
Central Region
Buikwe 11,723 12 46291 47.5 39,505 15.1 97,519 100
Bukomansimbi 5,987 17.5 21617 63.1 6,629 12.1 34,233 100
Butambala 2,324 10.7 9373 43.3 9,947 15.3 21,644 100
Buvuma 2,589 10.3 11167 44.5 11,341 15.5 25,097 100
Gomba 4,188 11.9 17825 50.7 13,124 13.9 35,137 100
Kalangala 2,793 13.9 8939 44.6 8,296 13.9 20,028 100
Kalungu 5,804 14 24198 58.5 11,339 12.5 41,341 100
Kampala 58,511 14.2 151286 36.6 203,625 19.3 413,422 100
Kayunga 8,276 10.9 43094 56.8 24,504 12.3 75,874 100
Kiboga 4,825 14.2 16412 48.4 12,672 13.1 33,909 100
Kyankwanzi 5,458 11.5 23542 49.5 18,591 12.9 47,591 100
Kyotera
Luwero 12,184 11.6 45991 43.9 46,602 13.9 104,777 100
Lwengo 7,811 12.7 35679 57.8 18,223 14.7 61,713 100
Lyantonde 2,597 12.6 12298 59.7 5,692 14.5 20,587 100
Masaka 9,583 12.7 32086 42.5 33,805 18.1 75,474 100
Mityana 9,298 11.7 35760 45 34,416 13.7 79,474 100
Mpigi 7,131 11.8 22930 38 30,258 15.9 60,319 100
Mubende 14,862 9.9 77059 51.2 58,668 12.9 150,589 100
Mukono 19,897 13.8 64764 45 59,121 15.7 143,782 100
Nakaseke 5,575 13 19681 45.9 17,659 14.5 42,915 100
Nakasongola 3,446 9.4 14065 38.5 19,003 13.7 36,514 100
Rakai 10,755 9.3 67170 57.9 38,142 15.1 116,067 100
Ssembabule 7,331 13.3 34658 62.8 13,206 13.1 55,195 100
Wakiso 53,667 10.7 176602 35.3 269,915 20.3 500,184 100
Eastern Region
Amuria 6,891 14.3 31910 66.2 9,374 11.5 48,175 100
Budaka 1,516 4.1 24655 66.4 10,967 13.3 37,138 100
Bududa 4,672 12.7 18981 51.6 13,130 15.7 36,783 100 Bugiri 4,499 6 47153 63.4 22,741 14.3 74,393 100
Bukedea 2,736 7.5 26264 72.2 7,398 11.9 36,398 100
Bukwo 841 5.1 3218 19.4 12,543 17.3 16,602 100 Bulambuli 2,325 6.9 13021 38.4 18,569 17.9 33,915 100 Busia 4,057 6.3 37878 58.6 22,669 16.7 64,604 100 Butaleja 2,038 4.6 29816 67.3 12,440 15.3 44,294 100 Buyende 2,826 4.6 40952 67 17,311 13.1 61,089 100
Iganga 7,210 7 45891 44.9 49,208 16.5 102,309 100
Appendices xxiv
District 1 Meal 2 Meals 3 or more meals Total households
Number Percent Number Percent Number Percent Number Percent
Eastern Region
Jinja 11,079 10.5 47107 44.8 46,976 17.7 105,162 100
Kaberamaido 2,252 5.8 27531 71.1 8,945 11.5 38,728 100
Kaliro 1,830 4.3 26518 61.8 14,537 15.3 42,885 100
Kamuli 6,257 6.7 52216 55.8 35,046 16.9 93,519 100
Kapchorwa 1,230 5.7 5310 24.8 14,914 16.5 21,454 100
Katakwi 8,722 28.5 17847 58.2 4,070 11.1 30,639 100
Kibuku 1,448 4.1 24015 67.8 9,969 13.7 35,432 100
Kumi 3,865 9.5 27074 66.5 9,804 12.5 40,743 100
Kween 696 3.9 3927 22 13,216 17.3 17,839 100
Luuka 2,499 5.6 27099 61.2 14,681 14.7 44,279 100
Manafwa 5,854 8.1 35287 48.5 31,564 15.7 72,705 100
Mayuge 5,141 5.4 55279 58.1 34,697 15.7 95,117 100
Mbale 10,202 9.4 45476 42 52,676 18.9 108,354 100
Namayingo 4,167 9.7 24754 57.5 14,132 13.9 43,053 100
Namisindwa
Namutumba 2,030 4.5 27077 59.8 16,175 15.3 45,282 100
Ngora 2,757 11.6 15629 66 5,296 12.5 23,682 100
Pallisa 3,491 5.3 46218 70.6 15,791 13.1 65,500 100
Serere 5,345 11.2 30525 64.1 11,780 11.9 47,650 100
Sironko 6,151 11 24260 43.5 25,342 17.7 55,753 100
Soroti 4,225 7.7 32125 58.5 18,521 14.7 54,871 100
Tororo 6,269 6.1 64341 62.9 31,714 16.5 102,324 100
Northern Region
Abim 9,978 55.2 6192 34.3 1,894 10.7 18,064 100
Adjumani 7,785 18.9 25635 62.1 7,842 11.5 41,262 100
Agago 13,883 32 26432 61 3,009 11.1 43,324 100
Alebtong 6,407 13.9 35526 76.9 4,261 10.9 46,194 100
Amolatar 1,329 4.8 19408 69.4 7,234 11.1 27,971 100
Amudat 3,014 19.5 9996 64.5 2,484 12.1 15,494 100
Amuru 11,011 30.1 21922 59.9 3,655 11.1 36,588 100
Apac 5,754 8 56271 78.6 9,536 10.9 71,561 100
Arua 17,412 11.9 61859 42.2 67,193 14.5 146,464 100
Dokolo 1,355 3.9 27685 79.3 5,856 11.1 34,896 100
Gulu 10,305 18.6 27807 50.2 17,251 11.7 55,363 100
Kaabong 6,986 24 19672 67.4 2,508 10.9 29,166 100
Kitgum 9,504 24 24474 61.8 5,613 11.1 39,591 100
Koboko 1654 5.5 7593 25.1 21,016 15.7 30,253 100
Kole 5,063 10.4 38294 79 5,121 10.7 48,478 100
13,841 52.9 9805 37.5 2,520 11.1 26,166 100 Kotido
Appendices xxv
District 1 Meal 2 Meals 3 or more meals Total households
Number Percent Number Percent Number Percent Number Percent
Northern Region
Lamwo 3,029 11 21869 79.7 2,538 10.9 27,436 100
10,193 11.5 51958 58.4 26,809 12.1 88,960 100 Lira Maracha 2,946 8.1 18692 51.6 14,617 12.5 36,255 100
Moroto 11,256 51.1 7921 36 2,835 11.3 22,012 100
Moyo 2,817 10.9 13343 51.6 9,674 12.1 25,834 100
Nakapiripirit 8,623 34 13146 51.8 3,605 11.9 25,374 100
Napak 14,050 52 11149 41.3 1,803 10.9 27,002 100
Nebbi 13,664 17.7 43753 56.6 19,920 13.7 77,337 100
Nwoya 4,923 18.8 17692 67.7 3,532 11.1 26,147 100
Omoro 5,528 17.5 21220 67.3 4,805 11.1 31,553 100
Otuke 7,327 33.4 13231 60.3 1,380 10.5 21,938 100
Oyam 7,185 9.4 56955 74.5 12,287 11.1 76,427 100
Pader 7,294 21.4 23053 67.6 3,766 11.3 34,113 100 Packwach
6,663 10.5 27206 42.7 29,866 13.9 63,735 100 Yumbe Zombo 4,036 7.7 25825 49 22,831 13.7 52,692 100
Western Region
Buhweju 2,179 8.8 16642 66.9 6,060 11.7 24,881 100
Buliisa 1,641 7.6 8564 39.7 11,355 15.7 21,560 100
Bundibugyo 3,363 7.5 13627 30.5 27,706 13.5 44,696 100
Bushenyi 3,982 7.8 30161 58.7 17,197 16.3 51,340 100
Hoima 7,290 5.8 42581 34 75,254 14.1 125,125 100
Ibanda 3,418 6.2 33477 61.1 17,853 13.5 54,748 100
Kabale 6,523 8.8 45906 61.7 21,978 13.1 74,407 100
Kabarole 7,832 7.3 38043 35.5 61,152 13.5 107,027 100
Kagadi 3,951 5.3 32867 44.4 37,190 12.5 74,008 100
Kakumiro 4,119 6.5 33045 52.2 26,182 12.3 63,346 100
Kamwenge 6,587 7.4 55241 62.3 26,857 12.9 88,685 100
Kanungu 4,364 7.8 31851 56.9 19,729 13.1 55,944 100
Kasese 7,976 5.7 55921 40.2 75,267 15.5 139,164 100
Kibaale 1,469 4.8 12323 40.3 16,810 12.3 30,602 100
Kiruhura 7,806 11.6 40991 61.2 18,224 13.7 67,021 100
Kiryandongo 3,289 6.3 28335 54.4 20,503 12.5 52,127 100
Kyegegwa 3,793 6.3 35032 58.5 21,086 12.5 59,911 100
Kyenjojo 6,590 7.2 43443 47.6 41,211 12.1 91,244 100
Masindi 3,254 5 20916 32.4 40,465 14.5 64,635 100 100 Mbarara 9,353 8.3 64532 57.3 38,752 17.7 112,637
Appendices xxvi
District 1 Meal 2 Meals 3 or more meals Total households
Number Percent Number Percent Number Percent Number Percent
Western Region
Mitooma 3,555 8.9 27577 69.3 8,643 13.1 39,775 100
Ntoroko 1,187 8.6 6361 45.8 6,330 14.9 13,878 100
Ntungamo 10,670 10.5 63472 62.4 27,517 13.3 101,659 100
Rubanda 3,385 7.8 30909 71.4 8,997 11.9 43,291 100
Rubirizi 2,717 9.5 18291 63.8 7,668 13.5 28,676 100
Rukungiri 5,162 7.4 39183 56.4 25,147 13.5 69,492 100
Sheema 3,129 6.8 29279 63.9 13,379 15.1 45,787 100
Total 792,707 10.9 3785049 51.9 2,713,021 37.2 7,290,777 100
Appendices xxvii
Table A.8: Consumption of Sugar and availability of salt in the Household
Consumed sugar at least once a day Salt available Number of District Percent Number of Households Percent Total Households Households Central Region
Buikwe 85.1 83,301 94.6 92,579 97,833
Bukomansimbi 72.9 25,021 95.5 32,780 34,328
Butambala 82.4 17,866 95.9 20,786 21,678
Buvuma 78.5 19,708 89.0 22,358 25,119
Gomba 66.2 23,337 95.3 33,573 35,240
Kalangala 87.6 17,548 92.6 18,555 20,041
Kalungu 80.6 33,392 96.3 39,865 41,405
Kampala 95.5 395,613 96.2 398,514 414,406
Kayunga 77.5 58,872 95.0 72,152 75,962
Kiboga 63.4 21,572 95.0 32,311 34,010
Kyankwanzi 61.4 29,300 94.6 45,121 47,687
Luwero 81.4 85,659 96.7 101,722 105,209
Lwengo 73.9 45,631 96.6 59,635 61,753
Lyantonde 56.9 11,725 95.6 19,723 20,623
Masaka 87.8 66,303 95.7 72,252 75,494
Mityana 77.7 61,899 96.3 76,706 79,665
Mpigi 80.6 48,694 95.0 57,381 60,388
Mubende 65.1 98,432 96.5 145,802 151,100
Mukono 87.1 125,560 95.9 138,293 144,160
Nakaseke 79.6 34,285 96.4 41,502 43,048
Nakasongola 74.5 27,263 94.4 34,578 36,610
Rakai 74.9 87,161 96.6 112,466 116,390
Ssembabule 59.6 32,995 95.6 52,911 55,330
Wakiso 93.9 470,662 97.0 486,245 501,463
Eastern Region
Amuria 56.0 27,003 91.5 44,136 48,234
Budaka 67.8 25,197 92.9 34,553 37,188
Bududa 89.8 33,086 93.8 34,553 36,848
Bugiri 75.0 55,870 93.6 69,717 74,469
Bukedea 68.2 24,849 91.3 33,248 36,415
Bukwo 92.7 15,404 93.3 15,506 16,617
Bulambuli 92.7 31,495 95.1 32,301 33,978
Busia 70.7 45,769 91.7 59,395 64,769
Butaleja 68.4 30,344 93.0 41,264 44,362
Buyende 72.8 44,533 92.9 56,877 61,199
Iganga 89.1 91,286 94.8 97,142 102,472
Appendices xxviii
Consumed sugar at least once a day Salt available Number of District Percent Number of Households Percent Total Households Households Eastern Region Jinja 90.0 94,795 96.1 101,219 105,358
Kaberamaido 64.1 24,863 93.4 36,192 38,760
Kaliro 79.3 34,024 95.1 40,820 42,924
81.8 76,654 95.0 89,050 93,690 Kamuli Kapchorwa 93.1 20,015 94.2 20,245 21,496
Katakwi 60.5 18,613 89.4 27,476 30,744
Kibuku 71.2 25,255 95.1 33,699 35,446
Kumi 72.2 29,413 94.1 38,350 40,748
Kween 93.7 16,727 95.2 16,994 17,859
Luuka 84.4 37,434 95.9 42,524 44,359
Manafwa 87.6 63,806 93.6 68,173 72,815
Mayuge 81.0 77,221 94.3 89,907 95,340
Mbale 91.5 99,327 94.1 102,182 108,558
Namayingo 68.8 29,631 92.3 39,780 43,096
Namutumba 79.0 35,859 95.8 43,444 45,371 Ngora 69.0 16,344 91.7 21,727 23,683 Pallisa 66.7 43,777 92.3 60,572 65,651
Serere 68.5 32,690 94.0 44,871 47,736
Sironko 91.6 51,143 92.4 51,609 55,862
Soroti 67.7 37,155 93.3 51,268 54,921
Tororo 75.1 76,943 92.8 95,097 102,492
Northern Region
Abim 39.3 7,104 82.8 14,966 18,082
Adjumani 56.4 23,284 88.6 36,596 41,315
Agago 36.0 15,637 88.3 38,297 43,376
Alebtong 59.3 27,425 93.8 43,355 46,228
Amolatar 76.2 21,322 93.9 26,292 27,994
Amudat 70.2 10,880 84.8 13,143 15,504
Amuru 45.6 16,704 90.6 33,210 36,650
Apac 58.1 41,595 92.5 66,251 71,620
Arua 71.2 104,352 95.5 140,090 146,627
Dokolo 65.4 22,857 94.6 33,059 34,957 Gulu 76.1 42,163 95.1 52,706 55,441 Kaabong 22.4 6,542 80.1 23,376 29,182
Kitgum 40.4 16,023 90.5 35,931 39,697
Koboko 78.6 23,808 92.4 27,972 30,271
Kole 65.5 31,787 94.1 45,647 48,525
Appendices xxix
Consumed sugar at once a day Salt available Number of District Percent Number of Households Percent Total Households Households Northern Region
Kotido 19.5 5,109 69.3 18,138 26,181
Lamwo 29.8 8,182 86.1 23,642 27,468
Lira 76.8 68,378 92.9 82,685 89,015
Maracha 55.9 20,261 93.1 33,757 36,272
Moroto 37.0 8,162 75.6 16,691 22,066
Moyo 66.6 17,219 95.8 24,787 25,867
Nakapiripirit 41.5 10,537 84.6 21,490 25,401
Napak 29.0 7,845 78.1 21,130 27,048
Nebbi 43.1 33,355 86.4 66,916 77,435
Nwoya 55.2 14,468 91.9 24,098 26,211
Omoro 60.1 18,979 95.1 30,020 31,572
Otuke 46.0 10,100 88.0 19,309 21,945
Oyam 63.6 48,677 94.5 72,313 76,536
Pader 43.4 14,831 88.7 30,328 34,183
Yumbe 73.8 47,047 92.2 58,787 63,773
Zombo 39.5 20,818 92.2 48,582 52,720
Western Region
Buhweju 42.8 10,662 96.7 24,101 24,912
Buliisa 64.7 13,983 88.4 19,097 21,602
Bundibugyo 74.8 33,474 89.1 39,905 44,778
Bushenyi 63.4 32,576 97.1 49,863 51,370
Hoima 67.2 84,307 95.4 119,683 125,399
Ibanda 56.8 31,198 96.6 53,072 54,947
Isingiro 43.5 44,171 93.5 95,002 101,623
Kabale 53.2 39,619 95.6 71,217 74,477
Kabarole 77.3 82,914 95.1 101,972 107,204
Kagadi 53.8 39,926 95.5 70,838 74,144
Kakumiro 56.7 35,983 97.4 61,818 63,471
Kamwenge 41.2 36,636 95.3 84,782 88,967
Kanungu 44.7 25,085 94.5 52,982 56,056
Kasese 66.6 92,856 93.8 130,728 139,406
Kibaale 57.1 17,474 97.9 29,953 30,608
Kiruhura 45.0 30,248 95.4 64,058 67,152
Kiryandongo 73.2 38,200 94.4 49,260 52,170
Kisoro 45.4 28,244 93.1 57,984 62,248
Kyegegwa 50.4 30,273 95.7 57,473 60,042 91,444 Kyenjojo 54.2 49,526 94.7 86,619
Appendices xxx
consumed sugar at least once a day Salt available Number of District Percent Number of Households Percent Total Households Households Western Region
Masindi 80.5 52,202 96.7 62,701 64,820
Mbarara 65.3 73,691 96.4 108,747 112,772
Mitooma 37.4 14,873 94.8 37,714 39,800
Ntoroko 72.3 10,059 91.1 12,675 13,917
Ntungamo 48.2 49,073 95.7 97,404 101,759
Rubanda 34.2 14,798 95.9 41,564 43,323
Rubirizi 64.1 18,431 96.9 27,862 28,748
Rukungiri 46.5 32,311 95.4 66,326 69,535
Sheema 56.9 26,075 97.5 44,687 45,812
Total 70.4 5,142,643 94.3 6,885,352 7,304,070
Appendices xxxi
Table A.9: Distribution of households by type of bathroom and use of soap for bathing
Type of Bathroom Use soap for bathing
Outside Outside District Inside, Inside, no built, built, no Make drainage drainage None Other Total Number Percent drainage drainage shift provided provided provided provided Central Region
Buikwe 6.1 1.8 43.4 20.1 19.0 8.0 1.6 100 94,158 96.2
Bukomansimbi 7.0 3.2 28.4 20.7 23.1 16.3 1.3 100 32,459 94.6
Butambala 6.4 2.6 41.5 23.3 15.0 10.1 1.0 100 20,633 95.2
Buvuma 1.3 1.4 6.3 9.2 24.4 49.7 7.6 100 23,677 94.3
Gomba 5.2 1.7 21.4 15.1 35 20.9 0.7 100 34,084 96.7
Kalangala 2.9 3.7 15.2 15.1 23.7 35.1 4.2 100 19,499 97.3
Kalungu 7.6 2.8 31.0 17.0 23.8 16.7 1.1 100 39,991 96.6
Kampala 20.6 2.2 60.5 13.2 1.8 1.3 0.4 100 407,864 98.4
Kayunga 2.9 1.4 32.2 20.1 31 10.8 1.6 100 72,848 95.9
Kiboga 4.6 1.6 30.6 20.1 26.8 13.7 2.5 100 32,851 96.6
Kyankwanzi 2.4 1.5 18.6 18.2 35.7 21.3 2.3 100 45,637 95.7
Kyotera 7.0 5.8 28.8 20.1 19.1 17.2 2.1 100 51,702 97.1
Luwero 5.6 1.9 44.1 19.3 18.1 9.9 1.2 100 102,205 97.1
Lwengo 6.2 4.1 27.9 20.8 22.3 17.0 1.7 100 59,864 96.9
Lyantonde 4.0 1.8 29.6 21.0 26.3 16.5 0.7 100 19,826 96.1
Masaka 11.0 3.8 39.3 15.5 13.6 15.3 1.4 100 73,444 97.3
Mityana 5.8 2.3 33.5 18.2 24.8 14.3 1.2 100 77,256 97.0
Mpigi 6.2 3.4 39.3 17.1 18.9 13 2.1 100 57,841 95.8
Mubende 3.0 1.6 22.8 21.5 31.4 17.4 2.2 100 145,503 96.3
Mukono 8.1 3.0 47.0 2.00 12.0 7.7 2.2 100 139,073 96.5
Nakaseke 4.7 3.2 34.3 22.8 21.5 11.9 1.7 100 41,619 96.7
Nakasongola 3.9 4.0 25.7 14.7 23.0 25.5 3.2 100 35,484 96.9
Rakai 3.2 4.0 17.9 20.6 30.7 21.2 2.2 100 60,049 95.1
Ssembabule 3.8 4.0 23.3 20.9 27.1 19.4 1.4 100 52,892 95.6
Wakiso 16.0 3.2 59.9 13.3 4.5 2.5 0.6 100 490,836 97.9
Eastern Region
Amuria 2.2 1.8 13.9 13.1 49.3 17.7 1.9 100 44,861 93
Budaka 2.6 1.2 49.2 29.8 10.7 5.8 0.7 100 34,985 94.1
Bududa 3.7 1.3 21.7 10 45.1 17.2 1 100 35,478 96.3
Bugiri 2.3 1.6 30.9 29 21.2 13.6 1.4 100 70,779 95
Bukedea 2.2 1.4 22.5 20.5 37.7 13.5 2.2 100 34,804 95.6
Bukwo 2.7 2.7 26.3 17.5 37.8 12.5 0.5 100 16,010 96.3
Bulambuli 2.1 2.1 21.1 17.6 42.8 13.1 1.2 100 32,874 96.8
Appendices xxxii
Type of Bathroom Use soap for bathing
Outside Outside District Inside, Inside, no built, built, no Make drainage drainage None Other Total Number Percent drainage drainage shift provided provided provided provided Eastern Region
Busia 4.3 1.4 29.1 14.5 37.4 12.2 1.0 100 62,495 96.5
Butaleja 3.2 1.4 28.1 21.9 35.5 8.9 1.0 100 40,792 92
Butebo 3.2 2 45.5 32.4 10.1 5.5 1.3 100 23,516 94.4
Buyende 2.6 1.7 33.9 26.2 18.6 14.6 2.4 100 57,636 94.2
Iganga 2.9 1.8 47.3 27.9 12 6.8 1.2 100 98,779 96.4
Jinja 9.5 1.9 44.2 19.7 18.1 5.4 1.2 100 102,229 97
Kaberamaido 2.6 1.4 12.9 12.9 45.3 22.9 2 100 36,383 93.9
Kaliro 2.2 1.4 46.5 32.6 8.4 8.0 1.0 100 41,135 95.8
Kamuli 2.6 2.4 34.8 23.2 24.1 11.2 1.7 100 89,394 95.4
Kapchorwa 2.6 1.9 24.7 17.8 41.9 9.8 1.3 100 20,622 95.9
Katakwi 1.9 1.7 11.6 13.8 54.8 14.2 1.9 100 28,284 92
Kibuku 2.2 1.3 46.5 34.8 7.9 6.1 1.2 100 33,862 95.5
Kumi 2.3 3.1 24.9 20.7 35.3 12.2 1.5 100 39,059 95.9
Kween 2.5 2.1 22.2 18.9 38.4 14.9 0.9 100 17,154 96.1
Luuka 1.8 1.1 40.1 27.3 20.4 8.3 1 100 42,864 96.6
Manafwa 4.6 2 22.6 11.6 47.3 10.7 1.1 100 29,850 96.4
Mayuge 2.9 2.2 35.8 28 15.9 12.2 3 100 90,556 95
Mbale 7.6 1.9 34.3 21.2 28.6 5.3 1.1 100 104,514 96.3
Namayingo 2.2 2.6 16.5 20 30.2 25.5 3.1 100 41,132 95.4
Namisindwa 2.5 1.3 25.5 15.6 34.6 18.3 2.2 100 40,124 95.9
Namutumba 2.2 1.9 39.2 29.3 17.9 8.5 1 100 43,252 95.3
Ngora 2.6 1.3 26.2 18.8 39.9 9.9 1.3 100 22,446 94.8
Pallisa 3.3 2.5 38.2 34.2 14.4 6.5 1.1 100 37,563 92.2
Serere 2.7 1.4 18.1 15.4 48.2 13.3 1.1 100 44,390 93
Sironko 2.9 1.1 17.8 12.5 53.6 11.4 0.8 100 53,495 95.8
Soroti 5.7 2.2 31.2 16.7 31.9 9.9 2.5 100 51,471 93.7
Tororo 5.6 1.4 24.6 17 42.8 7.4 1.1 100 97,473 95.1
Northern Region
Abim 2.7 3.5 22.5 17.8 31.8 18.6 3.1 100 15,113 83.6
Adjumani 3.3 3.7 42 22.2 11.1 13.9 3.8 100 35,793 86.6
Agago 5.6 4.1 22.9 13.6 13 37.1 3.7 100 37,928 87.4
Alebtong 2.8 2.6 27.9 21.7 25 18.5 1.6 100 43,360 93.8
Amolatar 2.8 2.1 23.7 20.4 28.7 20.8 1.5 100 26,705 95.4
Amudat 1.8 2.6 8 11.6 19.6 47.8 8.6 100 11,957 77.1
Amuru 4 4 23.2 18.5 19.2 27.1 3.9 100 32,006 87.3
Apac 3.1 2.3 23.2 20.2 34 15.7 1.5 100 67,241 93.9
Appendices xxxiii
Type of Bathroom Use soap for bathing
Outside Outside District Inside, Inside, no built, built, no Make drainage drainage None Other Total Number Percent drainage drainage shift provided provided provided provided Northern Region
Arua 4.4 2.5 43.5 24.1 9.5 14.5 1.5 100 139,827 95.4
Dokolo 2.1 1.2 42.8 23.2 17.9 11.8 1 100 33,391 95.5
Gulu 6 3.1 47.3 17.5 13.2 11.4 1.5 100 52,981 95.6
Kaabong 1.3 1.2 6.5 8.7 39.1 36.6 6.7 100 14,441 49.5
Kitgum 4.7 4.5 29.7 15.2 10.6 30.8 4.4 100 33,813 85.2
Koboko 5 2.5 41.8 24 13.5 11.8 1.3 100 27,925 92.3
Kole 2.2 3.3 23.7 22.1 33 14.1 1.5 100 46,374 95.6
Kotido 2 1.6 8.3 8.2 19.3 51.7 8.9 100 11,205 42.8
Lamwo 3.4 4.2 19.2 14.1 19.3 35.6 4.2 100 22,252 81
Lira 5.7 2.7 50 19.2 12.1 9.1 1.2 100 85,040 95.5
Maracha 1.6 1.5 45.6 27 5.6 18 0.7 100 33,982 93.7
Moroto 4.1 0.7 7.6 8.7 18.3 47.4 13.2 100 12,835 58.2
Moyo 2.7 1.5 51.1 19.3 17.6 6.6 1.2 100 24,697 95.5
Nakapiripirit 1.3 1.1 3.8 9 41.3 37.5 6 100 16,595 65.3
Napak 0.7 1.3 5.6 12.7 30.5 42.3 7 100 15,174 56.1
Nebbi 3.2 1.4 46.9 18.8 8.3 20 1.5 100 39,363 82.7
Nwoya 2.4 3.3 15.5 15.6 19 41.9 2.3 100 24,082 91.9
Omoro 3.9 4.2 17.4 16.8 26 28.7 3 100 29,828 94.5
Otuke 1.5 2 23.1 17.1 30.5 24.3 1.6 100 19,937 90.8
Oyam 2.7 2.2 21.1 17.4 41.2 13.3 2 100 72,733 95
Pader 4.4 3.8 25.8 16.7 15.7 29.9 3.8 100 29,231 85.5
Pakwach 1.8 1.5 20.7 14.1 33.8 26.6 1.6 100 26,146 87.6
Yumbe 4.1 2.1 46.2 23.3 12.7 9.3 2.3 100 56,991 89.4
Zombo 2.7 1.8 31.8 24.7 9.2 27.9 1.9 100 49,437 93.8
Western Region
Buhweju 2.2 0.7 9.4 13 54.1 20.3 0.4 100 24,163 97
Buliisa 1.9 1.7 14.8 13.7 36.3 28.2 3.5 100 20,254 93.8
Bundibugyo 2.4 1.9 23.2 20.3 34.8 15.7 1.7 100 41,023 91.6
Bunyangabu 2 0.8 16.2 19.2 46.4 14.7 0.7 100 34,754 96.4
Bushenyi 6.8 1.5 23.1 12.7 47.9 7.6 0.4 100 50,334 98
Hoima 3.3 1.4 18.2 14 27.9 33.2 1.9 100 120,584 96.2
Ibanda 4.2 1.2 19.9 14.3 45.7 12.9 1.8 100 53,737 97.8
Isingiro 3.1 1.5 14.8 14.3 45.6 19.6 1.2 100 94,842 93.3
Kabale 4.6 1.4 24.6 15.9 42.9 10.2 0.5 100 49,920 96.5
Kabarole 5 0.9 24.2 14.3 41.4 13.2 1.2 100 68,708 96.6
Kagadi 1.9 1.2 16.4 17.1 30.6 31.1 1.7 100 71,823 96.9
Appendices xxxiv
Type of Bathroom Use soap for bathing
Outside Outside District Inside, Inside, no built, built, no Make drainage drainage None Other Total Number Percent drainage drainage shift provided provided provided provided Western Region
Kakumiro 1.8 1.2 14.2 17.4 25.5 38.1 1.9 100 62,138 97.9
Kamwenge 1.6 1.1 11.8 14.6 46.6 22.8 1.4 100 84,668 95.2
Kanungu 3.2 1.3 22.7 19.6 26.3 26.2 0.7 100 53,580 95.6
Kasese 4.8 1.7 20.8 19.6 27.2 25 0.9 100 131,785 94.5
Kibaale 1.7 1.4 14 14.9 24.7 41.1 2.3 100 30,161 98.5
Kiruhura 2.9 1.4 20.1 17.3 37.5 15.2 5.5 100 64,863 96.6
Kiryandongo 3.4 2.4 26.4 18.1 23.9 24.2 1.7 100 49,720 95.3
Kisoro 4.2 2.4 16.4 16.4 35.4 23.8 1.3 100 59,603 95.8
Kyegegwa 1.3 1.1 12.8 15.5 37.4 27.5 4.5 100 57,568 95.9
Kyenjojo 1.7 0.9 15.4 14.4 42.9 21.9 2.8 100 87,889 96.1
Masindi 4.6 2.1 33.7 15.4 19.1 21.2 3.8 100 63,464 97.9
Mbarara 7.9 1.4 30.7 14.5 36.5 8 1 100 109,628 97.2
Mitooma 3 0.8 10 6.6 67.2 11.6 0.8 100 38,184 95.9
Ntoroko 0.8 1.1 15.6 11.5 42.3 25.7 3 100 12,924 92.9
Ntungamo 2.6 0.8 15.9 14.5 52.1 13.3 0.8 100 98,002 96.3
Rubanda 1.5 0.7 13.1 16.4 55.3 12.4 0.8 100 41,618 96.1
Rubirizi 3.7 2.4 17.5 15 42.3 18.8 0.3 100 27,891 97
Rukiga 2.3 1.1 12.8 14.7 58.1 10.3 0.6 100 21,782 95.9
Rukungiri 3.1 0.8 20.3 16.5 38 20.4 0.9 100 66,456 95.6
Sheema 4.9 1.3 20.1 12.4 54 6.9 0.4 100 44,489 97.1
Uganda 5.7 2.1 31.9 18.1 25.5 15.0 1.7 100 6,916,494 94.7
Appendices xxxv
Table A.10: Infant Mortality, Under Five Mortality and Life Expectancy at Birth by District
District Infant Mortality Under Five Mortality Life Expectancy at Birth
Male Female Total Male Female Total Male Female Total
Central Region
Kalangala 77 55 65 118 86 102 57.0 63.2 60.1
Kampala 36 25 31 48 33 41 67.8 72.5 70.2
Kiboga 52 62 58 76 99 88 63.2 61.3 62.2
Luwero 37 43 40 50 65 57 67.5 66.7 67.1
Masaka 57 42 50 85 62 74 61.8 67.2 64.5
Mpigi 43 35 39 60 49 55 65.7 69.4 67.6
Mubende 69 61 65 104 98 101 59.0 61.4 60.2
Mukono 39 30 35 53 41 48 66.9 71.0 68.9
Nakasongola 44 48 46 62 73 68 65.4 65.3 65.3
Rakai 99 66 81 156 105 130 52.1 60.3 56.2
Ssembabule 71 73 72 109 120 114 58.3 58.2 58.2
Kayunga 48 48 48 69 74 71 64.4 65.2 64.8
Wakiso 37 31 34 49 43 46 67.6 70.5 69.1
Lyantonde 98 79 88 156 131 143 52.1 56.6 54.4
Mityana 47 51 49 67 79 73 64.5 64.3 64.4
Nakaseke 42 32 37 58 44 52 66.0 70.3 68.2
Buikwe 49 41 45 70 61 65 64.2 67.4 65.8
Bukomansimbi 59 49 54 88 74 81 61.3 65.1 63.2
Butambala 61 45 52 91 67 78 60.8 66.3 63.6
Buvuma 44 45 45 62 68 65 65.4 66.2 65.8
Gomba 66 49 57 99 74 86 59.7 65.2 62.4
Kalungu 76 60 68 117 95 105 57.1 61.8 59.4
Kyankwanzi 79 50 65 122 78 101 56.4 64.6 60.5
Lwengo 93 53 72 147 82 113 53.2 63.9 58.6
Kyotera 87 51 68 135 79 106 54.7 64.3 59.5
Eastern Region
Bugiri 60 50 55 89 76 83 61.2 64.8 63.0
Busia 61 52 56 90 80 85 61.0 64.2 62.6
Iganga 55 54 54 81 84 82 62.4 63.6 63.0
Jinja 36 29 32 48 39 43 67.7 71.5 69.6
Kamuli 47 42 44 67 62 64 64.7 67.1 65.9
Kapchorwa 70 41 56 107 60 85 58.5 67.5 63.0
Katakwi 41 40 41 57 58 58 66.3 67.8 67.0
Kumi 32 28 30 41 38 40 69.0 71.6 70.3
Mbale 41 29 35 57 40 48 66.3 71.3 68.8
Appendices xxxvi
District Infant Mortality Under Five Mortality Life Expectancy at Birth
Male Female Total Male Female Total Male Female Total
Eastern Region
Pallisa 35 38 36 46 55 50 68.1 68.4 68.3
Soroti 40 35 37 55 49 52 66.5 69.5 68.0
Tororo 52 49 37 76 76 51 63.1 64.9 64.0
Kaberamaido 47 33 40 66 46 56 64.7 70.0 67.4
Mayuge 46 42 44 65 62 63 65.0 67.2 66.1
Sironko 49 43 46 70 63 67 64.1 67.0 65.5
Amuria 45 36 41 63 52 58 65.2 68.9 67.1
Budaka 68 58 63 103 91 97 59.1 62.4 60.8
Bududa 47 30 39 67 41 54 64.7 70.9 67.8
Bukedea 35 40 37 46 58 52 68.2 67.8 68.0
Bukwo 54 41 48 79 61 71 62.6 67.4 65.0
Butaleja 69 58 64 105 91 99 58.8 62.5 60.6
Kaliro 59 49 54 88 74 81 61.3 65.2 63.2
Manafwa 64 62 54 96 99 81 60.2 61.2 60.7
Namutumba 77 64 70 119 101 110 56.9 60.8 58.9
Bulambuli 40 41 40 54 61 57 66.8 67.3 67.1
Buyende 51 52 52 74 81 77 63.4 64.1 63.8
Kibuku 48 46 47 68 69 69 64.4 66.0 65.2
Kween 69 37 53 105 53 80 58.8 68.7 63.8
Luuka 56 43 50 82 63 73 62.2 67.0 64.6
Namayingo 65 57 61 98 89 94 59.9 62.8 61.3
Ngora 37 35 36 50 49 50 67.4 69.5 68.5
Serere 40 40 40 54 59 57 66.8 67.6 67.2
Butebo 43 50 46 59 76 67 65.9 64.8 65.4
Namisindwa 72 56 64 110 89 99 58.1 62.8 60.5
Northern Region
Adjumani 39 54 47 53 83 68 66.9 63.7 65.3
Apac 51 47 49 74 71 72 64.4 65.6 65.0
Arua 68 65 67 102 105 104 59.7 60.3 60.0
Gulu 50 38 44 73 55 64 59.7 68.4 64.0
Kitgum 31 30 30 40 40 10 70.8 71.1 70.9
Kotido 32 31 32 41 42 42 70.4 70.7 70.6
Lira 69 43 56 105 63 85 59.2 66.9 63.1
Moroto 32 60 46 41 94 67 70.4 61.9 66.1
Moyo 87 42 64 136 62 98 54.6 67.2 60.9
Nebbi 69 58 63 104 91 98 59.4 62.5 60.9
Nakapiripirit 30 26 28 38 34 36 71.2 72.5 71.8
Appendices xxxvii
District Infant Mortality Under Five Mortality Life Expectancy at Birth
Male Female Total Male Female Total Male Female Total
Northern Region
Pader 30 67 49 39 108 72 70.9 59.9 65.4
Yumbe 38 29 34 52 40 46 68.3 71.2 69.8
Abim 62 45 55 92 68 83 61.3 66.2 63.8
Amolatar 52 54 53 75 83 79 64.2 63.7 63.9
Amuru 42 32 38 59 45 53 67.0 70.2 68.6
Dokolo 77 40 59 118 59 90 57.3 67.7 62.5
Kaabong 48 24 35 69 31 47 65.2 73.3 69.2
Koboko 48 53 51 69 82 75 65.3 63.9 64.6
Maracha 79 57 68 121 90 107 56.8 62.6 59.7
Oyam 45 46 46 63 69 66 66.2 66.0 66.1
Agago 40 59 49 55 94 73 67.8 62.0 64.9
Alebtong 82 57 70 127 90 109 56.0 62.6 59.3
Amudat 41 21 29 56 27 38 67.6 74.5 71.0
Kole 53 50 51 77 76 77 63.8 64.8 64.3
Lamwo 63 54 58 94 84 89 61.1 63.6 62.3
Napak 14 16 15 17 21 19 77.0 76.1 76.6
Nwoya 61 29 15 91 39 19 61.6 71.4 66.5
Otuke 72 55 63 109 85 98 58.6 63.3 61.0
Zombo 77 86 82 119 143 130 57.1 54.9 56.0
Omoro 42 62 52 58 98 77 66.2 61.4 63.8
Pakwach 70 57 64 107 90 98 59.0 62.7 60.9
Western Region
Bundibugyo 72 54 63 110 84 97 58.4 63.5 61.0
Bushenyi 37 22 29 50 28 38 68.7 74.1 71.4
Hoima 50 43 46 72 63 68 64.7 67.0 65.9
Kabale 42 37 53 58 53 80 67.1 68.8 68.0
Kabarole 39 40 40 53 59 56 68.0 67.8 67.9
Kasese 51 45 48 73 67 70 64.5 66.3 65.4
Kibaale 63 52 58 95 80 88 60.9 64.2 62.6
Kisoro 24 21 23 30 27 29 73.0 74.3 73.6
Masindi 54 37 45 79 52 66 63.5 68.8 66.2
Mbarara 48 42 45 69 62 65 65.3 67.1 66.2
Ntungamo 82 49 64 127 74 99 56.0 65.2 60.6
Rukungiri 33 73 52 43 119 78 70.1 58.3 64.2
Kamwenge 83 67 75 129 108 119 55.7 59.9 57.8
Kanungu 37 54 46 50 85 67 68.7 63.4 66.0
Appendices xxxviii
District Infant Mortality Under Five Mortality Life Expectancy at Birth
Male Female Total Male Female Total Male Female Total
Western Region
Kyenjojo 62 52 57 93 81 87 61.2 64.0 62.6
Buliisa 89 69 80 140 112 127 54.1 59.3 56.7
Ibanda 65 50 58 97 78 89 60.6 64.6 62.6
Isingiro 81 50 66 125 78 102 56.2 64.6 60.4
Kiruhura 57 58 58 84 92 88 62.6 62.3 62.5
Buhweju 92 66 79 144 107 127 53.5 60.1 56.8
Kiryandongo 62 51 56 92 78 85 61.4 64.5 62.9
Kyegegwa 96 65 80 152 103 128 52.3 60.5 56.4
Mitooma 58 54 56 85 84 85 62.5 63.5 63.0
Ntoroko 44 49 46 61 75 68 66.6 65.0 65.8
Rubirizi 83 75 78 128 122 125 55.8 57.9 56.8
Sheema 46 38 42 65 54 67 66.0 68.5 67.3
Kagadi 73 64 68 111 102 107 58.3 60.7 59.5
Kakumiro 78 67 72 120 108 114 57.0 59.9 58.4
Rubanda 57 68 63 85 109 97 62.5 59.7 61.1
Bunyangabu 37 30 34 50 41 45 68.7 71.1 69.9
Rukiga 62 54 58 93 84 89 61.2 63.5 62.4
0.0
UGANDA 54 46 50 79 69 74 62.8 64.5 63.7
Appendices xxxix
List of Contributors to this thematic report Uganda Bureau of Statistics Management Ben Paul Mungyereza, Executive Director Imelda Atai Musana, Deputy Executive Director- Statistical Production and Development Vitus Mulindwa Kato, Deputy Executive Director- Corporate Services
Authors Pamela Nabukhonzo Kakande, Uganda Bureau of Statistics Tony Odonkonyero, Economic Policy Research Centre- Makerere University
Reviewers John Ssebuliba Ssekamate (Ph.D), National Planning Authority Allen Kabagyenyi (Ph.D), Centre for Population and Applied Statistics- Makerere University Edith Akiror, United Nations Population Fund Helen Namirembe Nviiri, Uganda Bureau of Statistics Ronald Sombwe, Uganda Bureau of Statistics Alfred Geresom Musamali, Uganda Bureau of Statistics Anthony Kalule Tamusuza, Independent Consultant Andrew L Mukulu, Independent Consultant
Data Analyst Wilson Nyegenye, Uganda Bureau of Statistics Johnstone Galande, Uganda Bureau of Statistics Lawrence Mugula, Uganda Bureau of Statistics
GIS Specialist Charles Adriku, Uganda Bureau of Statistics Design and Typesetting Cover Tukaheebwa T Francis, 2ka.com Interior Deogracious Mutyaba, Uganda Bureau of Statistics
Health Status and Associated Factors xl
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The Household Questionnaire and Codelist for the National Population and Housing Census 2014
Health Status and Associated Factors xlii
Health Status and Associated Factors xliii
Health Status and Associated Factors xliv
Health Status and Associated Factors xlv
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Health Status and Associated Factors xlvii
Health Status and Associated Factors xlviii
DISTRICT OF PREVIOUS RESIDENCE (P12) H7-H13, H17 Central Eastern Northern Western Country of Previous Distance Conversion 101 Kalangala 201 Bugiri 301 Adjumani 401 Bundibugyo Residence 1 mile = 1.6 km 102 Kampala 202 Busia 302 Apac 402 Bushenyi 671 Kenya Mile Km Mile Km 103 Kiboga 203 Iganga 303 Arua 403 Hoima 672 Tanzania 0.5 = 0.8 16.5 = 26.4 104 Luwero 204 Jinja 304 Gulu 404 Kabale 673 Rwanda 1.0 = 1.6 17.0 = 27.2 105 Masaka 205 Kamuli 305 Kitgum 405 Kabarole 674 Burundi 1.5 = 2.4 17.5 = 28.0 106 Mpigi 206 Kapchorwa 306 Kotido 406 Kasese 675 South Sudan 2.0 = 3.2 18.0 = 28.8 107 Mubende 207 Katakwi 307 Lira 407 Kibaale 676 Dem. Rep. Of 2.5 = 4.0 18.5 = 29.6 108 Mukono 208 Kumi 308 Moroto 408 Kisoro Congo 3.0 = 4.8 19.0 = 30.4 109 Nakasongola 209 Mbale 309 Moyo 409 Masindi 677 Somalia 3.5 = 5.6 19.5 = 31.2 110 Rakai 210 Pallisa 310 Nebbi 410 Mbarara 678 Other Africa 4.0 = 6.4 20.0 = 32.0 111 Sembabule 211 Soroti 311 Nakapiripirit 411 Ntungamo 681 United Kingdom 4.5 = 7.2 20.5 = 32.8 112 Kayunga 212 Tororo 312 Pader 412 Rukungiri 682 Other Europe 5.0 = 8.0 21.0 = 33.6 113 Wakiso 213 Kaberamaido 313 Yumbe 413 Kamwenge 683 Asia 684 USA 5.5 = 8.8 21.5 = 34.4 114 Lyantonde 214 Mayuge 314 Abim 414 Kanungu 685 Canada 6.0 = 9.6 22.0 = 35.2 115 Mityana 215 Sironko 315 Amolatar 415 Kyenjojo 686 Central & Latin 6.5 = 10.4 22.5 = 36.0 116 Nakaseke 216 Amuria 316 Amuru 416 Buliisa America 7.0 = 11.2 23.0 = 36.8 117 Buikwe 217 Budaka 317 Dokolo 417 Ibanda 687 Australia 7.5 = 12.0 23.5 = 37.6 118 Bukomasimbi 218 Bududa Kaabong 418 Isingiro 688 Oceania 8.0 = 12.8 24.0 = 38.4 119 Butambala 318 219 Bukedea 319 Koboko 419 Kiruhura 689 Non-Ugandan-Not 8.5 = 13.6 24.5 = 39.2 120 Buvuma Stated 9.0 = 14.4 25.0 = 40.0 220 Bukwo 320 Maracha 420 Buhweju 121 Gomba 9.5 = 15.2 25.5 = 40.8 221 Butaleja 321 Oyam 421 Kiryandongo 122 Kalungu 10.0 = 16.0 26.0 = 41.6 222 Kaliro 322 Agago 422 Kyegegwa 123 Kyankwanzi 10.5 = 16.8 26.5 = 42.4 223 Manafwa 323 Alebtong 423 Mitooma 124 Lwengo 11.0 = 17.6 27.0 = 43.2 224 Namutumba 324 Amudat 424 Ntoroko 11.5 = 18.4 27.5 = 44.0 225 Bulambuli 325 Kole 425 Rubirizi 12.0 = 19.2 28.0 = 44.8 226 Buyende 326 Lamwo 426 Sheema 12.5 = 20.0 28.5 = 45.6 227 Kibuku 327 Napak 13.0 = 20.8 29.0 = 46.4 228 Kween 328 Nwoya 13.5 = 21.6 29.5 = 47.2 229 Luuka Otuke 329 14.0 = 22.4 30.0 = 48.0 230 Namayingo 330 Zombo 14.5 = 23.2 30.5 = 48.8 231 Ngora 15.0 = 24.0 31.0 = 49.6 232 Serere 15.5 = 24.8 31.5 = 50.4 16.0 = 25.6 32.0 = 51.2
Health Status and Associated Factors xlix
i Health Sector Development plan for 2015/16 -2019/20 ii http://www.worldbank.org/hnppublications. Determinants and Consequences of High Fertility: A Synopsis of the Evidence. June 2010 iii Naomi J. Spence. The Long-Term Consequences of Childbearing: Physical and Psychological Well-Being of Mothers in Later Life iv P vi vii viii ix Monroy De Velasco A. Consequences of early childbearing. Draper Fund Rep. 1982 Dec;(11):26-7. x Uganda Bureau of Statistics (UBOS) and ICF. 2017. Uganda Demographic and Health Survey 2016: Key Indicators Report. Kampala, Uganda: UBOS, and Rockville, Maryland, USA: UBOS and ICF. xi World Health Organization. Making health services adolescent friendly. Developing national quality standards for adolescent friendly health services. ly primary-care services: how are we doing and what more needs to be done. The Lancet, 2007, 369. xiii Uganda Bureau of Statistics. Uganda National Household Survey 2016/17 xiv SDG indicators Metadata repository. https://unstats.un.org/sdgs/metadata/ xv UN Principles and Recommendations for population and Housing census xvi Taylor RS1, Ashton KE, Moxham T, Hooper L, Ebrahim S. Reduced dietary salt for the prevention of cardiovascular disease: a meta-analysis of randomized controlled trials (Cochrane review). dium and Potassium Excretion and Risk of Cardiovascular Events
Uganda Bureau of Statistics (UBOS) and ICF. 2012. Uganda Demographic and Health Survey 2011: Main Report. Kampala, Uganda: UBOS, and Rockville, Maryland, USA: UBOS and ICF.